Tootfinder

Statistical Insight into Meta-Learning via Predictor Subspace Characterization and Quantification of Task Diversity
Saptati Datta, Nicolas W. Hengartner, Yulia Pimonova, Natalie E. Klein, Nicholas Lubbers
https://arxiv.org/abs/2509.18349

Statistical Insight into Meta-Learning via Predictor Subspace Characterization and Quantification of Task Diversity
Meta-learning has emerged as a powerful paradigm for leveraging information across related tasks to improve predictive performance on new tasks. In this paper, we propose a statistical framework for analyzing meta-learning through the lens of predictor subspace characterization and quantification of task diversity. Specifically, we model the shared structure across tasks using a latent subspace and introduce a measure of diversity that captures heterogeneity across task-specific predictors. We …

Diversity Boosts AI-Generated Text Detection
Advik Raj Basani, Pin-Yu Chen
https://arxiv.org/abs/2509.18880 https://arxiv.org/pdf/2509.18880

🥨 Germany’s anti-diversity backlash isn’t fatigue – it’s strategy masquerading as neutrality | Fatma Aydemir
https://www.theguardian.com/commentisfree/2025/sep/30/germany-anti-diversity-backlash-trump-afd

Measuring Prosody Diversity in Zero-Shot TTS: A New Metric, Benchmark, and Exploration
Yifan Yang, Bing Han, Hui Wang, Long Zhou, Wei Wang, Mingyu Cui, Xu Tan, Xie Chen
https://arxiv.org/abs/2509.19928

Measuring Prosody Diversity in Zero-Shot TTS: A New Metric, Benchmark, and Exploration
Prosody diversity is essential for achieving naturalness and expressiveness in zero-shot text-to-speech (TTS). However, frequently used acoustic metrics capture only partial views of prosodic variation and correlate poorly with human perception, leaving the problem of reliably quantifying prosody diversity underexplored. To bridge this gap, we introduce ProsodyEval, a prosody diversity assessment dataset that provides Prosody Mean Opinion Score (PMOS) alongside conventional acoustic metrics. Pr…

Dear Leader has a very North Korean vibe going...
Trump Officials Demand George Mason’s President Apologize Over Diversity - The New York Times
https://www.nytimes.com/2025/08/22/us/george-mason-president-diversity-investigation.html

Diversity mitigates polarization and consensus in opinion dynamics
Sidharth Pradhan, Sangeeta Rani Ujjwal
https://arxiv.org/abs/2509.19860 https://arxiv.or…

Diversity mitigates polarization and consensus in opinion dynamics
We study the opinion dynamics in a population by considering a variant of Kuramoto model where the phase of an oscillator represents the opinion of an individual on a single topic. Two extreme phases separated by $π$ represent opposing views. Any other phase is considered as an intermediate opinion between the two extremes. The interaction (or attitude) between two individuals depends on the difference between their opinions and can be positive (attractive) or negative (repulsive) based on the…

Similarity as Thermodynamic Work: Between Depth and Diversity -- from Information Distance to Ugly Duckling
Kentaro Imafuku
https://arxiv.org/abs/2509.16236 https://

Similarity as Thermodynamic Work: Between Depth and Diversity -- from Information Distance to Ugly Duckling
Defining similarity is a fundamental challenge in information science. Watanabe's Ugly Duckling Theorem highlights diversity, while algorithmic information theory emphasizes depth through Information Distance. We propose a statistical-mechanical framework that treats program length as energy, with a temperature parameter unifying these two aspects: in the low-temperature limit, similarity approaches Information Distance; in the high-temperature limit, it recovers the indiscriminability of the U…

AgentInit: Initializing LLM-based Multi-Agent Systems via Diversity and Expertise Orchestration for Effective and Efficient Collaboration
Chunhao Tian, Yutong Wang, Xuebo Liu, Zhexuan Wang, Liang Ding, Miao Zhang, Min Zhang
https://arxiv.org/abs/2509.19236

Chunked Data Shapley: A Scalable Dataset Quality Assessment for Machine Learning
Andreas Loizou, Dimitrios Tsoumakos
https://arxiv.org/abs/2508.16255 https://

Chunked Data Shapley: A Scalable Dataset Quality Assessment for Machine Learning
As the volume and diversity of available datasets continue to increase, assessing data quality has become crucial for reliable and efficient Machine Learning analytics. A modern, game-theoretic approach for evaluating data quality is the notion of Data Shapley which quantifies the value of individual data points within a dataset. State-of-the-art methods to scale the NP-hard Shapley computation also face severe challenges when applied to large-scale datasets, limiting their practical use. In th…

Why the Raiders are all in on building a new legacy with Las Vegas HBCU Classic https://www.nytimes.com/athletic/6742095/2025/10/24/why-the-raiders-are-all-in-on-building-a-new-legacy-with-las-vegas-hbcu-classic/

Peeling metric spaces of strict negative type
Steve Huntsman
https://arxiv.org/abs/2509.19565 https://arxiv.org/pdf/2509.19565

Peeling metric spaces of strict negative type
We describe a unified and computationally tractable framework for finding outliers in, and maximum-diversity subsets of, finite metric spaces of strict negative type. Examples of such spaces include finite subsets of Euclidean space and finite subsets of a sphere without antipodal points. The latter accounts for state-of-the-art text embeddings, and we apply our framework in this context to sketch a hallucination mitigation strategy and separately to a class of path diversity optimization probl…

Towards Robust In-Context Learning for Medical Image Segmentation via Data Synthesis
Jiesi Hu, Yanwu Yang, Zhiyu Ye, Chenfei Ye, Hanyang Peng, Jianfeng Cao, Ting Ma
https://arxiv.org/abs/2509.19711

Towards Robust In-Context Learning for Medical Image Segmentation via Data Synthesis
The rise of In-Context Learning (ICL) for universal medical image segmentation has introduced an unprecedented demand for large-scale, diverse datasets for training, exacerbating the long-standing problem of data scarcity. While data synthesis offers a promising solution, existing methods often fail to simultaneously achieve both high data diversity and a domain distribution suitable for medical data. To bridge this gap, we propose \textbf{SynthICL}, a novel data synthesis framework built upon …

Retrieval-Augmented Defense: Adaptive and Controllable Jailbreak Prevention for Large Language Models
Guangyu Yang, Jinghong Chen, Jingbiao Mei, Weizhe Lin, Bill Byrne
https://arxiv.org/abs/2508.16406 …

Retrieval-Augmented Defense: Adaptive and Controllable Jailbreak Prevention for Large Language Models
Large Language Models (LLMs) remain vulnerable to jailbreak attacks, which attempt to elicit harmful responses from LLMs. The evolving nature and diversity of these attacks pose many challenges for defense systems, including (1) adaptation to counter emerging attack strategies without costly retraining, and (2) control of the trade-off between safety and utility. To address these challenges, we propose Retrieval-Augmented Defense (RAD), a novel framework for jailbreak detection that incorporate…

'No better time than now': Justin Fargas embraces coaching opportunity with the Silver and Black https://www.raiders.com/news/justin-fargas-embraces-coaching-opportunity-with-the-silver-and-black

Adaptive Articulated Object Manipulation On The Fly with Foundation Model Reasoning and Part Grounding
Xiaojie Zhang, Yuanfei Wang, Ruihai Wu, Kunqi Xu, Yu Li, Liuyu Xiang, Hao Dong, Zhaofeng He
https://arxiv.org/abs/2507.18276

Adaptive Articulated Object Manipulation On The Fly with Foundation Model Reasoning and Part Grounding
Articulated objects pose diverse manipulation challenges for robots. Since their internal structures are not directly observable, robots must adaptively explore and refine actions to generate successful manipulation trajectories. While existing works have attempted cross-category generalization in adaptive articulated object manipulation, two major challenges persist: (1) the geometric diversity of real-world articulated objects complicates visual perception and understanding, and (2) variation…

BloomIntent: Automating Search Evaluation with LLM-Generated Fine-Grained User Intents
Yoonseo Choi, Eunhye Kim, Hyunwoo Kim, Donghyun Park, Honggu Lee, Jinyoung Kim, Juho Kim
https://arxiv.org/abs/2509.18641

BloomIntent: Automating Search Evaluation with LLM-Generated Fine-Grained User Intents
If 100 people issue the same search query, they may have 100 different goals. While existing work on user-centric AI evaluation highlights the importance of aligning systems with fine-grained user intents, current search evaluation methods struggle to represent and assess this diversity. We introduce BloomIntent, a user-centric search evaluation method that uses user intents as the evaluation unit. BloomIntent first generates a set of plausible, fine-grained search intents grounded on taxonomie…

Late-surviving New Mexican #dinosaurs illuminate high end-Cretaceous diversity and provinciality: https://www.science.org/doi/10.1126/science.adw3282 ->
Dinosaurs were thriving until asteroid struck, research suggests: https://www.theguardian.com/science/2025/oct/23/dinosaurs-asteroid-struck-research - dating of rock formation in New Mexico casts doubt on theory that species was already in decline.

Learning Progression-Guided AI Evaluation of Scientific Models To Support Diverse Multi-Modal Understanding in NGSS Classroom
Leonora Kaldaras, Tingting Li, Prudence Djagba, Kevin Haudek, Joseph Krajcik
https://arxiv.org/abs/2509.18157

Learning Progression-Guided AI Evaluation of Scientific Models To Support Diverse Multi-Modal Understanding in NGSS Classroom
Learning Progressions (LPs) can help adjust instruction to individual learners needs if the LPs reflect diverse ways of thinking about a construct being measured, and if the LP-aligned assessments meaningfully measure this diversity. The process of doing science is inherently multi-modal with scientists utilizing drawings, writing and other modalities to explain phenomena. Thus, fostering deep science understanding requires supporting students in using multiple modalities when explaining phenom…

UN treaty to protect oceans gains enough ratifications to become international law in 2026, crucial for safeguarding marine ecosystems and combating climate change. #climatechange #climatesolutions #climate

"UN Treaty To Protect Oceans To Take Effect After Clinching Ratification
"A UN treaty to protect marine diversity in the high seas was struck Friday after Morocco and Sierra Leone ratified the agreement, clinching the threshold of at least 60 ratifications needed to enact it as international law."

Joint Channel Estimation and Computation Offloading in Fluid Antenna-assisted MEC Networks
Ying Ju, Mingdong Li, Haoyu Wang, Lei Liu, Youyang Qu, Mianxiong Dong, Victor C. M. Leung, Chau Yuen
https://arxiv.org/abs/2509.19340

Joint Channel Estimation and Computation Offloading in Fluid Antenna-assisted MEC Networks
With the emergence of fluid antenna (FA) in wireless communications, the capability to dynamically adjust port positions offers substantial benefits in spatial diversity and spectrum efficiency, which are particularly valuable for mobile edge computing (MEC) systems. Therefore, we propose an FA-assisted MEC offloading framework to minimize system delay. This framework faces two severe challenges, which are the complexity of channel estimation due to dynamic port configuration and the inherent n…

A Jarque-Bera test for skew normal data
Diam Ba, Gorgui Gning, Gandasor Bonyiri Onesiphore Da, Oumar Foly Sow, Gane Samb Lo
https://arxiv.org/abs/2507.18032 https://

A Jarque-Bera test for skew normal data
The skew normal law has been introduced in Azzalin (1985) as an alternative to adjusting asymmetric data that share important patterns with the normal law. It has been extensively studied. However, there is so much to do in order to catch the diversity and the richness of the investigation of its normal counterpart. The General Jarque-Berra Test (GJBT) has been devised by Lo et al. (2015), Da et al. (2023) for arbitrary laws with at least finite first eight moments, as a generalization of the J…

Implicit reporting standards in bibliometric research: what can reviewers' comments tell us about reporting completeness?
Dimity Stephen, Alexander Schniedermann, Andrey Lovakov, Marion Schmidt, Matteo Ottaviani, Nikita Sorgatz, Roberto Cruz Romero, Torger M\"oller, Valeria Aman, Stephan Stahlschmidt
https://arxiv.org/abs/2508.162…

Implicit reporting standards in bibliometric research: what can reviewers' comments tell us about reporting completeness?
The recent surge in bibliometric studies published has been accompanied by increasing diversity in the completeness of reporting these studies' details, affecting reliability, reproducibility, and robustness. Our study systematises the reporting of bibliometric research using open peer reviews. We examined 182 peer reviews of 85 bibliometric studies published in library and information science (LIS) journals and conference proceedings, and non-LIS journals. We extracted 968 reviewer comments an…

UN Peacekeeping Force in Lebanon Spends US Taxpayer Money on 'Gender Diversity' Training and Therapeutic Yoga Instruction, Drawing Scrutiny From Trump Admin (Adam Kredo/The Washington Free Beacon)
https://freebeacon.com/national-security/un-peacekeeping-force-in-lebanon-spends-us-taxpayer-money-on-gender-diversity-training-and-therapeutic-yoga-instruction-drawing-scrutiny-from-trump-admin/
http://www.memeorandum.com/250818/p3#a250818p3

Democratizing News Recommenders: Modeling Multiple Perspectives for News Candidate Generation with VQ-VAE
Hardy, Sebastian Pad\'o, Amelie W\"uhrl, Tanise Ceron
https://arxiv.org/abs/2508.13978

Democratizing News Recommenders: Modeling Multiple Perspectives for News Candidate Generation with VQ-VAE
Current News Recommender Systems based on past clicks are designed for engagement, but come at the cost of limiting diversity in the suggested content. While diversity-aware algorithms exist, they suffer from two major limitations. First, they fail to account for normative diversity, which requires fair access to a broad range of perspectives. Second, they typically apply diversity late in the system's pipeline, after a lot of content has already been filtered out. Both limitations confine thei…

MeerKAT discovery of 164 compact radio rings toward the Galactic Plane
C. Bordiu, F. Bufano, G. Umana, J. R. Rizzo, C. Spingola, C. Trigilio, S. Loru, M. D. Filipovic, C. Buemi, F. Cavallaro, L. Cerrigone, P. Leto, A. Ingallinera, S. Riggi, A. C. Ruggeri, Z. Smeaton, P. A. Woudt
https://arxiv.org/abs/2509.20289

MeerKAT discovery of 164 compact radio rings toward the Galactic Plane
We report the discovery of 164 compact (radius < 1 arcmin) radio rings using MeerKAT 1.3 GHz data from the SARAO MeerKAT Galactic Plane Survey (l=2-60deg, 252-358deg, |b|<1.5deg) and the Galactic Centre mosaic, from a search aimed at identifying previously uncatalogued radio sources. Within this sample, approximately 19 per cent of the rings contain a central point radio source. A multiwavelength analysis reveals a striking diversity: about 40 per cent of the rings enclose an isolated…

Diversity of Structured Domains via k-Kemeny Scores
Piotr Faliszewski, Krzysztof Sornat, Stanis{\l}aw Szufa, Tomasz W\k{a}s
https://arxiv.org/abs/2509.15812 https://

Diversity of Structured Domains via k-Kemeny Scores
In the k-Kemeny problem, we are given an ordinal election, i.e., a collection of votes ranking the candidates from best to worst, and we seek the smallest number of swaps of adjacent candidates that ensure that the election has at most k different rankings. We study this problem for a number of structured domains, including the single-peaked, single-crossing, group-separable, and Euclidean ones. We obtain two kinds of results: (1) We show that k-Kemeny remains intractable under most of these do…

UserRL: Training Interactive User-Centric Agent via Reinforcement Learning
Cheng Qian, Zuxin Liu, Akshara Prabhakar, Jielin Qiu, Zhiwei Liu, Haolin Chen, Shirley Kokane, Heng Ji, Weiran Yao, Shelby Heinecke, Silvio Savarese, Caiming Xiong, Huan Wang
https://arxiv.org/abs/2509.19736

UserRL: Training Interactive User-Centric Agent via Reinforcement Learning
Reinforcement learning (RL) has shown promise in training agentic models that move beyond static benchmarks to engage in dynamic, multi-turn interactions. Yet, the ultimate value of such agents lies in their ability to assist users, a setting where diversity and dynamics of user interaction pose challenges. In this work, we propose UserRL, a unified framework for training and evaluating user-centric abilities through standardized gym environments paired with simulated users. We systematically v…

Kuramoto Mean Field Game with Intrinsic Frequencies
Rene Carmona, Quentin Cormier, Mete Soner
https://arxiv.org/abs/2509.18000 https://arxiv.org/pdf/2509.1…

Kuramoto Mean Field Game with Intrinsic Frequencies
This paper studies a mean field game formulation of the classical Kuramoto model for synchronization. Our model captures the diversity within the population by considering random intrinsic frequencies, which allows us to study the impact of this heterogeneity on synchronization patterns and stability. Our findings contribute insights into the interplay between intrinsic frequency diversity and synchronization dynamics, offering a more realistic understanding of complex systems. The proposed fra…

Table Detection with Active Learning
Somraj Gautam, Nachiketa Purohit, Gaurav Harit
https://arxiv.org/abs/2509.20003 https://arxiv.org/pdf/2509.20003

Table Detection with Active Learning
Efficient data annotation remains a critical challenge in machine learning, particularly for object detection tasks requiring extensive labeled data. Active learning (AL) has emerged as a promising solution to minimize annotation costs by selecting the most informative samples. While traditional AL approaches primarily rely on uncertainty-based selection, recent advances suggest that incorporating diversity-based strategies can enhance sampling efficiency in object detection tasks. Our approach…

Cetvel: A Unified Benchmark for Evaluating Language Understanding, Generation and Cultural Capacity of LLMs for Turkish
Yakup Abrek Er, Ilker Kesen, G\"ozde G\"ul \c{S}ahin, Aykut Erdem
https://arxiv.org/abs/2508.16431

Cetvel: A Unified Benchmark for Evaluating Language Understanding, Generation and Cultural Capacity of LLMs for Turkish
We introduce Cetvel, a comprehensive benchmark designed to evaluate large language models (LLMs) in Turkish. Existing Turkish benchmarks often lack either task diversity or culturally relevant content, or both. Cetvel addresses these gaps by combining a broad range of both discriminative and generative tasks ensuring content that reflects the linguistic and cultural richness of Turkish language. Cetvel covers 23 tasks grouped into seven categories, including tasks such as grammatical error corr…

ICYMI yesterday: I've been writing about the diversity of tools for contributing to #OpenStreetMap and how this diversity plays a role in creating and maintaining a healthy commons.
https://tzovar.as/tool-diversity/

Atomistic Generative Diffusion for Materials Modeling
Nikolaj R{\o}nne, Bj{\o}rk Hammer
https://arxiv.org/abs/2507.18314 https://arxiv.org/pdf/2507.18314…

Atomistic Generative Diffusion for Materials Modeling
We present a generative modeling framework for atomistic systems that combines score-based diffusion for atomic positions with a novel continuous-time discrete diffusion process for atomic types. This approach enables flexible and physically grounded generation of atomic structures across chemical and structural domains. Applied to metallic clusters and two-dimensional materials using the QCD and C2DB datasets, our models achieve strong performance in fidelity and diversity, evaluated using pre…

Crosslisted article(s) found for quant-ph. https://arxiv.org/list/quant-ph/new
[1/2]:
- Similarity as Thermodynamic Work: Between Depth and Diversity -- from Information Distance to Ugl...
Kentaro Imafuku

MeAJOR Corpus: A Multi-Source Dataset for Phishing Email Detection
Paulo Mendes (GECAD, ISEP, Polytechnic of Porto, Portugal), Eva Maia (GECAD, ISEP, Polytechnic of Porto, Portugal), Isabel Pra\c{c}a (GECAD, ISEP, Polytechnic of Porto, Portugal)
https://arxiv.org/abs/2507.17978

MeAJOR Corpus: A Multi-Source Dataset for Phishing Email Detection
Phishing emails continue to pose a significant threat to cybersecurity by exploiting human vulnerabilities through deceptive content and malicious payloads. While Machine Learning (ML) models are effective at detecting phishing threats, their performance largely relies on the quality and diversity of the training data. This paper presents MeAJOR (Merged email Assets from Joint Open-source Repositories) Corpus, a novel, multi-source phishing email dataset designed to overcome critical limitation…

The far right is surging in the United States,
driven in part by white nationalists exploiting economic anxieties
and a populace increasingly frustrated with the political status quo.
Now, as the Trump administration rolls back diversity, equity and inclusion policies,
cracks down on immigration and offers pardons to white supremacists,
some see an opening.
In creating their community, the founders of "Return to the Land" are challenging anti-d…

Arkansas Housing Development Restricted to White Residents Sparks Legal Concerns
Housing rights experts say a community restricted to white residents is illegal, but the creators believe they could win a potential challenge in court in the current political climate.

Why the Raiders are all in on building a new legacy with Las Vegas HBCU Classic https://www.nytimes.com/athletic/6742095/2025/10/24/why-the-raiders-are-all-in-on-building-a-new-legacy-with-las-vegas-hbcu-classic/

A Unified and Predictive Measure of Functional Diversity
Adji Bousso Dieng, Amey Pasarkar
https://arxiv.org/abs/2509.16133 https://arxiv.org/pdf/2509.16133…

A Unified and Predictive Measure of Functional Diversity
Despite the critical role of functional diversity (FD) in understanding ecological systems and processes, its robust quantification remains a significant challenge. A long-held view in the field is that it is not possible to capture its three facets -- functional richness, functional divergence, and functional evenness -- in a single index. This perspective has prompted recent proposals for FD measurement to use three separate indices, one for each aspect. Here, we challenge this paradigm by de…

DIVEBATCH: Accelerating Model Training Through Gradient-Diversity Aware Batch Size Adaptation
Yuen Chen, Yian Wang, Hari Sundaram
https://arxiv.org/abs/2509.16173 https://

DIVEBATCH: Accelerating Model Training Through Gradient-Diversity Aware Batch Size Adaptation
The goal of this paper is to accelerate the training of machine learning models, a critical challenge since the training of large-scale deep neural models can be computationally expensive. Stochastic gradient descent (SGD) and its variants are widely used to train deep neural networks. In contrast to traditional approaches that focus on tuning the learning rate, we propose a novel adaptive batch size SGD algorithm, DiveBatch, that dynamically adjusts the batch size. Adapting the batch size is c…

Don't miss today's Metacurity for the critical infosec developments you should know, including
--DOGE killed $324 million in grants for cybersecurity diversity, global partners
--US is the top investor in global spyware,
--Kenyan authorities accused of installing spyware on filmmakers' phones,
--GOP senators press Zuckerberg on WhatsApp whistleblower's claims,
--Wyden accuses Microsoft of negligence in Ascension attack,
--CISA says CVE shoul…

DOGE killed $324 million in grants for cybersecurity diversity, global partners
US is the top investor in global spyware, Kenyan authorities accused of installing spyware on filmmakers' phones, GOP senators press Zuckerberg on WhatsApp whistleblower's claims, Wyden accuses Microsoft of negligence in Ascension attack, CISA says CVE should remain public, much more

Federal Gunmen Shoot Endangered Mexican Gray Wolf Pup, Target Second Wolf - Center for Biological Diversity
https://biologicaldiversity.org/w/news/press-releases/federal-gunmen-shoot-endangered-mexican-gray-wolf-pup-target-second-wolf-2025-08-21/

Constructive Conflict-Driven Multi-Agent Reinforcement Learning for Strategic Diversity
Yuxiang Mai, Qiyue Yin, Wancheng Ni, Pei Xu, Kaiqi Huang
https://arxiv.org/abs/2509.14276

Constructive Conflict-Driven Multi-Agent Reinforcement Learning for Strategic Diversity
In recent years, diversity has emerged as a useful mechanism to enhance the efficiency of multi-agent reinforcement learning (MARL). However, existing methods predominantly focus on designing policies based on individual agent characteristics, often neglecting the interplay and mutual influence among agents during policy formation. To address this gap, we propose Competitive Diversity through Constructive Conflict (CoDiCon), a novel approach that incorporates competitive incentives into coopera…

Moderate deviation principle for plug-in estimators of diversity indices on countable alphabets
Zhenhong Yu, Yu Miao
https://arxiv.org/abs/2508.12382 https://

Moderate deviation principle for plug-in estimators of diversity indices on countable alphabets
In the present paper, we consider the moderate deviation principle for the plug-in estimators of a large class of diversity indices on countable alphabets, where the distribution may change with the sample size. Our results cover some of the most commonly used indices, including Tsallis entropy, Reńyi entropy and Hill diversity number.

https://www.newscientist.com/article/mg26735551-500-enchanting-photos-of-bizarre-mushrooms-showcase-fungi-diversity/

Enchanting photos of 'bizarre' mushrooms showcase fungi diversity
From squat toadstools to web-like mushrooms, images from Funga Obscura celebrate some of the most striking fungi on our planet

Metasurface-based Fluid Antennas: from Electromagnetics to Communications Model
Pablo Ram\'irez-Espinosa, Cleof\'as Segura-G\'omez, \'Angel Palomares-Caballero, F. Javier L\'opez-Mart\'inez, David Morales-Jim\'enez
https://arxiv.org/abs/2507.17982

Metasurface-based Fluid Antennas: from Electromagnetics to Communications Model
Fluid antenna systems (FASs) have become a popular topic in the wireless community as an effective yet simple means of exploiting spatial diversity. Due to the limitations of physically moving radiating elements, electronically reconfigurable antennas are emerging as practical implementations of FASs, since changing the radiation pattern is functionally equivalent to physically moving the device. However, electronically reconfigurable antennas pose a challenge in terms of analytical modeling, o…

The Impact of Team Diversity in Agile Development Education
Marco Torchiano, Riccardo Coppola, Antonio Vetro', Xhoi Musaj
https://arxiv.org/abs/2509.08389 https://

The Impact of Team Diversity in Agile Development Education
Software Engineering is mostly a male-dominated sector, where gender diversity is a key feature for improving equality of opportunities, productivity, and innovation. Other diversity aspects, including but not limited to nationality and ethnicity, are often understudied.In this work we aim to assess the impact of team diversity, focusing mainly on gender and nationality, in the context of an agile software development project-based course. We analyzed 51 teams over three academic years, measuri…

A Versatile Foundation Model for AI-enabled Mammogram Interpretation
Fuxiang Huang, Jiayi Zhu, Yunfang Yu, Yu Xie, Yuan Guo, Qingcong Kong, Mingxiang Wu, Xinrui Jiang, Shu Yang, Jiabo Ma, Ziyi Liu, Zhe Xu, Zhixuan Chen, Yujie Tan, Zifan He, Luhui Mao, Xi Wang, Junlin Hou, Lei Zhang, Qiong Luo, Zhenhui Li, Herui Yao, Hao Chen
https://arxiv.…

A Versatile Foundation Model for AI-enabled Mammogram Interpretation
Breast cancer is the most commonly diagnosed cancer and the leading cause of cancer-related mortality in women globally. Mammography is essential for the early detection and diagnosis of breast lesions. Despite recent progress in foundation models (FMs) for mammogram analysis, their clinical translation remains constrained by several fundamental limitations, including insufficient diversity in training data, limited model generalizability, and a lack of comprehensive evaluation across clinicall…

Crosslisted article(s) found for nlin.AO. https://arxiv.org/list/nlin.AO/new
[1/1]:
- Diversity mitigates polarization and consensus in opinion dynamics
Sidharth Pradhan, Sangeeta Rani Ujjwal

"Snow leopard populations threatened by climate change and low genetic diversity"
#SnowLeopard #Leopard #Animals #Climate

Snow leopard habitats could be at risk from climate change
Because there aren’t many snow leopards left, they are classified as “vulnerable” on the IUCN Red List.

Trajectory Encryption Cooperative Salvo Guidance
Lohitvel Gopikannan, Shashi Ranjan Kumar, Abhinav Sinha
https://arxiv.org/abs/2509.17341 https://arxiv.org…

Trajectory Encryption Cooperative Salvo Guidance
This paper introduces the concept of trajectory encryption in cooperative simultaneous target interception, wherein heterogeneity in guidance principles across a team of unmanned autonomous systems is leveraged as a strategic design feature. By employing a mix of heterogeneous time-to-go formulations leading to a cooperative guidance strategy, the swarm of vehicles is able to generate diverse trajectory families. This diversity expands the feasible solution space for simultaneous target interce…

Benchmarking Gaslighting Attacks Against Speech Large Language Models
Jinyang Wu, Bin Zhu, Xiandong Zou, Qiquan Zhang, Xu Fang, Pan Zhou
https://arxiv.org/abs/2509.19858 https:/…

Benchmarking Gaslighting Attacks Against Speech Large Language Models
As Speech Large Language Models (Speech LLMs) become increasingly integrated into voice-based applications, ensuring their robustness against manipulative or adversarial input becomes critical. Although prior work has studied adversarial attacks in text-based LLMs and vision-language models, the unique cognitive and perceptual challenges of speech-based interaction remain underexplored. In contrast, speech presents inherent ambiguity, continuity, and perceptual diversity, which make adversarial…

Kalman Filtering-Assisted Node Deployment for Distributed OTFS-ISAC: A Geometry-Aware Design for the Joint Sensing and Communication
Jyotsna Rani, Kuntal Deka, Ganesh Prasad, Zilong Liu
https://arxiv.org/abs/2509.16700

Kalman Filtering-Assisted Node Deployment for Distributed OTFS-ISAC: A Geometry-Aware Design for the Joint Sensing and Communication
Integrated sensing and communication (ISAC) is a key enabler for next-generation wireless networks, offering spectrum efficiency and reduced hardware complexity. While monostatic ISAC has been well studied, its limited spatial diversity reduces reliability in high-mobility scenarios. Distributed ISAC alleviates this via cooperative nodes, but conventional OFDM-based designs remain vulnerable to Doppler shifts and multipath fading. Orthogonal time frequency space (OTFS) modulation has recently e…

Parameterized Algorithms for Diversity of Networks with Ecological Dependencies
Mark Jones, Jannik Schestag
https://arxiv.org/abs/2510.09512 https://arxiv.…

Parameterized Algorithms for Diversity of Networks with Ecological Dependencies
For a phylogenetic tree, the phylogenetic diversity of a set A of taxa is the total weight of edges on paths to A. Finding small sets of maximal diversity is crucial for conservation planning, as it indicates where limited resources can be invested most efficiently. In recent years, efficient algorithms have been developed to find sets of taxa that maximize phylogenetic diversity either in a phylogenetic network or in a phylogenetic tree subject to ecological constraints, such as a food web. Ho…

Migration is as old as time:
https://theconversation.com/two-seventh-century-people-found-with-west-african-ancestry-a-story-of-diversity-and-integration-in-early-anglo-saxon-socie…

Two seventh-century people found with west African ancestry – a story of diversity and integration in early Anglo-Saxon society
We should not be surprised that there are west Africans in early medieval Britain, the clues were there.

Identifying rocky planets and water worlds among sub-Neptune-sized exoplanets with the Habitable Worlds Observatory
Renyu Hu, Michiel Min, Max Millar-Blanchaer, Jacob Lustig-Yaeger, Tyler Robinson, Jennifer Burt, Athena Coustenis, Mario Damiano, Chuanfei Dong, Courtney Dressing, Luca Fossati, Stephen Kane, Soumil Kelkar, Tim Lichtenberg, Jean-Baptiste Ruffio, Dibyendu Sur, Armen Tokadjian, Martin Turbet

Identifying rocky planets and water worlds among sub-Neptune-sized exoplanets with the Habitable Worlds Observatory
Astronomers are debating whether the plentiful "sub-Neptune" exoplanets -- worlds a bit larger than Earth but smaller than Neptune -- are predominantly rocky planets, water-rich "ocean worlds," or gas-enshrouded mini-Neptunes. This question is crucial because such sub-Neptune-sized planets are among the most common in our galaxy, yet we have no analog in our own solar system, making them a key to understanding planet formation and diversity. It also directly impacts the search for habitable wor…

Think Landing a Job Is Hard? Try Having 'DEI' on Your Resume (Saijel Kishan/Bloomberg)
https://www.bloomberg.com/news/features/2025-10-20/dei-jobs-vanish-as-diversity-workers-struggle-to-land-roles
http://www.memeorandum.com/251020/p104#a251020p104

All political violence is bad; violence is never a good answer.
From report AG and potus want to hide: "…the number of far-right attacks continues to outpace all other types of terrorism and domestic violent extremism."
https://www.scribd.com/document/9186184…

What NIJ Research Tells Us About Domestic Terrorism | PDF | Extremism | Crimes
NIJ-funded research has enhanced understanding of domestic terrorism, particularly the rise of far-right extremist violence in the U.S., which has outpaced other forms of terrorism. The studies reveal that radicalization processes vary by group and crime type, and highlight the importance of community-based prevention strategies. Key findings include the diversity of extremist beliefs and behaviors, the role of military experience in radicalization, and the need for targeted interventions to pr…

Bird Twin: Research Group Leader (f/m/x) for Developing Models of Bird Diversity and Policy-relevant Applications in Germany at UFZ, Germany
#ecoevojobs #ecologyjobs #xp

Enhancing Transformer-Based Vision Models: Addressing Feature Map Anomalies Through Novel Optimization Strategies
Sumit Mamtani
https://arxiv.org/abs/2509.19687 https://

Enhancing Transformer-Based Vision Models: Addressing Feature Map Anomalies Through Novel Optimization Strategies
Vision Transformers (ViTs) have demonstrated superior performance across a wide range of computer vision tasks. However, structured noise artifacts in their feature maps hinder downstream applications such as segmentation and depth estimation. We propose two novel and lightweight optimisation techniques- Structured Token Augmentation (STA) and Adaptive Noise Filtering (ANF)- to improve interpretability and mitigate these artefacts. STA enhances token diversity through spatial perturbations duri…

Die ePetition 183357 an den Bundestag aus dem Bereich Migrationspolitik mit dem Titel
Einführung eines bundesweiten Visa-Lotterie-Programms nach Vorbild der Diversity Visa Lottery der Vereinigten Staaten
kann bis zum Mittwoch 01. Oktober 2025 01:00 UTC mitgezeichnet werden und lautet
Mit der Pet…

Die ePetition 183357 an den Bundestag aus dem Bereich Migrationspolitik mit dem Titel
Einführung eines bundesweiten Visa-Lotterie-Programms nach Vorbild der Diversity Visa Lottery der Vereinigten Staaten
kann bis zum Mittwoch 01. Oktober 2025 01:00 UTC mitgezeichnet werden und lautet
Mit der Pet…

Explosions of pulsating red supergiants: a natural pathway for the diversity of Type II-P/L supernovae
V. A. Bronner, E. Laplace, F. R. N. Schneider, Ph. Podsiadlowski
https://arxiv.org/abs/2508.11077 …

Explosions of pulsating red supergiants: a natural pathway for the diversity of Type II-P/L supernovae
Red supergiants (RSGs), which are progenitors of hydrogen-rich Type II supernovae (SNe), have been known to pulsate from both observations and theory. The pulsations can be present at core collapse and affect the resulting SN. However, SN light curve models of such RSGs commonly use hydrostatic progenitor models and ignore pulsations. Here, we model the final stages of a 15 solar-mass RSG and self-consistently follow the hydrodynamical evolution. We find the growth of large amplitude radial pul…

Analysis: journalism's DEI efforts in the US have declined, fueled in part by the Trump administration's quashing of diversity initiatives (Hanaa' Tameez/Nieman Lab)
https://www.niemanlab.org/2025/09/from-reckoning-to-retreat-news…

From reckoning to retreat: Journalism’s DEI efforts are in decline
Diversity-related newsroom jobs haven't totally disappeared — but they also haven't stuck.

M&M33: MUSE and M33 I. Unveiling the Diversity of HII Regions in M33 with MUSE
A. Feltre, F. Belfiore, G. Cresci, E. Corbelli, N. Tomi\v{c}i\'c, F. Mannucci, A. Marconi, E. Bertola, C. Bracci, M. Ceci, M. Curti, Q. D'Amato, M. Ginolfi, E. Koch, I. Lamperti, L. Magrini, C. Marconcini, A. Plat, M. Scialpi, G. Tozzi, L. Ulivi, G. Venturi, M. V. Zanchettin, A. Chakraborty, A. Amiri

M&M33: MUSE and M33 I. Unveiling the Diversity of HII Regions in M33 with MUSE
We present new VLT/MUSE mosaic observations of a 3 $\times$ 8 arcmin$^2$ area along the southern major axis of the nearby galaxy M33 at a distance of 840 kpc from the Milky Way. These data provide an unprecedented view of the galaxy interstellar medium (ISM), and allow us to resolve ionised nebulae at a spatial scale of $\approx$5 pc. We identify and catalogue 124 HII regions, down to H$α$ luminosities of $\approx 5\times$10$^{35}$ erg s$^{-1}$, one order of magnitude fainter than previous sur…

Quantitative metrics for trait and identity distributions
Leah Hoogstra, Katherine Slyman, Bjorn Sandstede
https://arxiv.org/abs/2509.14237 https://arxiv.o…

Quantitative metrics for trait and identity distributions
Understanding the role of demographic diversity in group settings requires effective quantitative metrics. Intersectional feminist theory has highlighted that demographic identities can intersect in complex ways, but most metrics used to study these traits are one-dimensional. In their paper "Diversity, identity, and data" (2025), Topaz et al. introduced two novel metrics that capture multiple aspects of demographic identities among group members: "intersecting diversity" and "shared identity".…

Impact of RHIs and ipSIC on Active RIS-NOMA Systems with Low-Precision ADCs
Qianqian Li, Hua Li, Shiya Hao, Lintao Li, Xiaoming Dai
https://arxiv.org/abs/2509.19383 https://

Impact of RHIs and ipSIC on Active RIS-NOMA Systems with Low-Precision ADCs
This study evaluates the performance of an active reconfigurable intelligent surface (ARIS)-assisted non-orthogonal multiple access (NOMA) system employing low-precision analog-to-digital converters (ADCs). Analytical approximations for the outage probability (OP) are derived, considering residual hardware impairments (RHIs) and imperfect successive interference cancellation (ipSIC). Additionally, we analyze the asymptotic OP, system throughput, and diversity order at high signal-to-noise ratio…

D-RDW: Diversity-Driven Random Walks for News Recommender Systems
Runze Li, Lucien Heitz, Oana Inel, Abraham Bernstein
https://arxiv.org/abs/2508.13035 https://

D-RDW: Diversity-Driven Random Walks for News Recommender Systems
This paper introduces Diversity-Driven RandomWalks (D-RDW), a lightweight algorithm and re-ranking technique that generates diverse news recommendations. D-RDW is a societal recommender, which combines the diversification capabilities of the traditional random walk algorithms with customizable target distributions of news article properties. In doing so, our model provides a transparent approach for editors to incorporate norms and values into the recommendation process. D-RDW shows enhanced pe…

Diversity in planetary architectures from pebble accretion: Water delivery to the habitable zone with pebble snow
Sean McCloat, Gijs Mulders, Sherry Fieber-Beyer
https://arxiv.org/abs/2509.14101

Diversity in planetary architectures from pebble accretion: Water delivery to the habitable zone with pebble snow
"Pebble snow" describes a planet formation mechanism where icy pebbles in the outer disk reach inner planet embryos as the water ice line evolves inward. We model the effects pebble snow has on sculpting planetary system architectures by developing "The PPOLs Model". The model is capable of growing any number of protoplanet seed masses by pebble accretion simultaneously and accounts for differences in rocky and icy pebble composition, the filtering of pebbles by other protoplanets, the pebble i…

MotionTrans: Human VR Data Enable Motion-Level Learning for Robotic Manipulation Policies
Chengbo Yuan, Rui Zhou, Mengzhen Liu, Yingdong Hu, Shengjie Wang, Li Yi, Chuan Wen, Shanghang Zhang, Yang Gao
https://arxiv.org/abs/2509.17759

MotionTrans: Human VR Data Enable Motion-Level Learning for Robotic Manipulation Policies
Scaling real robot data is a key bottleneck in imitation learning, leading to the use of auxiliary data for policy training. While other aspects of robotic manipulation such as image or language understanding may be learned from internet-based datasets, acquiring motion knowledge remains challenging. Human data, with its rich diversity of manipulation behaviors, offers a valuable resource for this purpose. While previous works show that using human data can bring benefits, such as improving rob…

Bayesian estimators of diversity indexes on exchangeable random partitions
Servet Martinez
https://arxiv.org/abs/2509.12115 https://arxiv.org/pdf/2509.1211…

Bayesian estimators of diversity indexes on exchangeable random partitions
Bayesian diversity estimators are martingales converging almost surely and in mean with common limit and local behavior with plug in estimators.

On The Road - To Xi’An/ Beings 👁️‍🗨️
在路上 - 去西安/ 灵 👁️‍🗨️
📷 Pentax MX
🎞️Kodak Double-X 5222
#filmphotography #Photography #blackandwhite

Weekend #Plankton Factoid 🦠🦐
You've likely watched a police procedural where the lab states the drowning was suspicious because of algae. The shells of diatoms have long been used in forensic #limnology because they are made of glass, so preserve very well.

A method for improving multilingual quality and diversity of instruction fine-tuning datasets
Chunguang Zhao, Yilun Liu, Pufan Zeng, Yuanchang Luo, Shimin Tao, Minggui He, Weibin Meng, Song Xu, Ziang Chen, Chen Liu, Hongxia Ma, Li Zhang, Boxing Chen, Daimeng Wei
https://arxiv.org/abs/2509.15549

A method for improving multilingual quality and diversity of instruction fine-tuning datasets
Multilingual Instruction Fine-Tuning (IFT) is essential for enabling large language models (LLMs) to generalize effectively across diverse linguistic and cultural contexts. However, the scarcity of high-quality multilingual training data and corresponding building method remains a critical bottleneck. While data selection has shown promise in English settings, existing methods often fail to generalize across languages due to reliance on simplistic heuristics or language-specific assumptions. In…

Following our mapping party for OpenStreetMap's birthday, I've been thinking more about the diversity of OSM tools and how they help create and maintain a commons.
#OpenStreetMap

Maximum diversity, weighting and invariants of time series
Byungchang So
https://arxiv.org/abs/2509.11146 https://arxiv.org/pdf/2509.11146

Maximum diversity, weighting and invariants of time series
Magnitude, obtained as a special case of Euler characteristic of enriched category, represents a sense of the size of metric spaces and is related to classical notions such as cardinality, dimension, and volume. While the studies have explained the meaning of magnitude from various perspectives, continuity also gives a valuable view of magnitude. Based on established results about continuity of magnitude and maximum diversity, this article focuses on continuity of weighting, a distribution whos…

DiCriTest: Testing Scenario Generation for Decision-Making Agents Considering Diversity and Criticality
Qitong Chu, Yufeng Yue, Danya Yao, Huaxin Pei
https://arxiv.org/abs/2508.11514

DiCriTest: Testing Scenario Generation for Decision-Making Agents Considering Diversity and Criticality
The growing deployment of decision-making agents in dynamic environments increases the demand for safety verification. While critical testing scenario generation has emerged as an appealing verification methodology, effectively balancing diversity and criticality remains a key challenge for existing methods, particularly due to local optima entrapment in high-dimensional scenario spaces. To address this limitation, we propose a dual-space guided testing framework that coordinates scenario param…

Harvard hiring investigation could upend employment practices for institutions well beyond academia (Aidan Ryan/The Boston Globe)
https://www.bostonglobe.com/2025/08/18/metro/harvard-trump-hiring-investigation-diversity/
http://www.memeorandum.com/250819/p60#a250819p60

Quantum MIMO Diversity over Discrete-Variable Crosstalk Channels
Shehbaz Tariq, Junaid ur Rehman, Symeon Chatzinotas
https://arxiv.org/abs/2508.07344 https://

Quantum MIMO Diversity over Discrete-Variable Crosstalk Channels
Quantum communication plays a pivotal role in enabling distributed quantum computing and sensing. Diversity strategies can be used to increase the communication reliability (in the sense of output fidelity with respect to the input quantum state) when multiple communication channels are available. The current paper proposes a diversity strategy for quantum discrete variable (DV) multiple-input-multiple-output (MIMO) channels, utilizing approximate cloning to distribute information across multip…

Generalized Adaptation-Induced Non-universal Synchronization Transitions in Random Hypergraphs
Sangita Dutta, Pinaki Pal, Chittaranjan Hens
https://arxiv.org/abs/2507.18421 http…

Generalized Adaptation-Induced Non-universal Synchronization Transitions in Random Hypergraphs
We investigate the effect of partial order parameter adaptation in form of general functions on the synchronization behavior of coupled Kuramoto oscillators on top of random hypergraph models. The interactions between the oscillators are considered as pairwise and triangular. Using the Ott-Antonsen ansatz, we obtain a set of self-consistent equations of the order parameter that describe the synchronization diagrams. A broad diversity of synchronization transitions are observed as a result of th…

The U.S. Department of Education has pulled funding for programs in eight states
aimed at supporting students who have both hearing and vision loss,
a move that could affect some of the country’s most vulnerable students.
The programs are considered vital in those states but represent only a little over $1 million a year in federal money.
Nonetheless, they got caught in the Trump administration’s attacks on diversity, equity and inclusion,
with an Education Dep…

Programs for Students With Hearing and Vision Loss Harmed by Trump’s Anti-Diversity Push
Citing concerns about DEI, the U.S. Department of Education has halted funding for programs that support students with combined hearing and vision loss in eight states. “How low can you go?” one advocate asked. “How can you do this to children?”

Empirical Evidences for the Effects of Feature Diversity in Open Set Recognition and Continual Learning
Jiawen Xu, Odej Kao
https://arxiv.org/abs/2508.13005 https://

Empirical Evidences for the Effects of Feature Diversity in Open Set Recognition and Continual Learning
Open set recognition (OSR) and continual learning are two critical challenges in machine learning, focusing respectively on detecting novel classes at inference time and updating models to incorporate the new classes. While many recent approaches have addressed these problems, particularly OSR, by heuristically promoting feature diversity, few studies have directly examined the role that feature diversity plays in tackling them. In this work, we provide empirical evidence that enhancing feature…

Informfully Recommenders -- Reproducibility Framework for Diversity-aware Intra-session Recommendations
Lucien Heitz, Runze Li, Oana Inel, Abraham Bernstein
https://arxiv.org/abs/2508.13019

Informfully Recommenders -- Reproducibility Framework for Diversity-aware Intra-session Recommendations
Norm-aware recommender systems have gained increased attention, especially for diversity optimization. The recommender systems community has well-established experimentation pipelines that support reproducible evaluations by facilitating models' benchmarking and comparisons against state-of-the-art methods. However, to the best of our knowledge, there is currently no reproducibility framework to support thorough norm-driven experimentation at the pre-processing, in-processing, post-processing, …

Kaepernick, Lynch join hockey diversity event https://www.espn.com/olympics/hockey/story/_/id/45869078/colin-kaepernick-marshawn-lynch-join-hockey-diversity-group-host-event

And another related position:
BirdFuture: Research Group Leader (f/m/x) for Developing Models of Bird Diversity and Policy-relevant Applications in Europe
#ecologyjobs #ecoevojobs #xp

Diversity-enhanced Collaborative Mamba for Semi-supervised Medical Image Segmentation
Shumeng Li, Jian Zhang, Lei Qi, Luping Zhou, Yinghuan Shi, Yang Gao
https://arxiv.org/abs/2508.13712

Diversity-enhanced Collaborative Mamba for Semi-supervised Medical Image Segmentation
Acquiring high-quality annotated data for medical image segmentation is tedious and costly. Semi-supervised segmentation techniques alleviate this burden by leveraging unlabeled data to generate pseudo labels. Recently, advanced state space models, represented by Mamba, have shown efficient handling of long-range dependencies. This drives us to explore their potential in semi-supervised medical image segmentation. In this paper, we propose a novel Diversity-enhanced Collaborative Mamba framewor…

CAST: Counterfactual Labels Improve Instruction Following in Vision-Language-Action Models
Catherine Glossop, William Chen, Arjun Bhorkar, Dhruv Shah, Sergey Levine
https://arxiv.org/abs/2508.13446

CAST: Counterfactual Labels Improve Instruction Following in Vision-Language-Action Models
Generalist robots should be able to understand and follow user instructions, but current vision-language-action (VLA) models struggle with following fine-grained commands despite providing a powerful architecture for mapping open-vocabulary natural language instructions to robot actions. One cause for this is a lack of semantic diversity and language grounding in existing robot datasets and, specifically, a lack of fine-grained task diversity for similar observations. To address this, we presen…

PuzzleClone: An SMT-Powered Framework for Synthesizing Verifiable Data
Kai Xiong, Yanwei Huang, Rongjunchen Zhang, Kun Chen, Haipang Wu
https://arxiv.org/abs/2508.15180 https://…

PuzzleClone: An SMT-Powered Framework for Synthesizing Verifiable Data
High-quality mathematical and logical datasets with verifiable answers are essential for strengthening the reasoning capabilities of large language models (LLMs). While recent data augmentation techniques have facilitated the creation of large-scale benchmarks, existing LLM-generated datasets often suffer from limited reliability, diversity, and scalability. To address these challenges, we introduce PuzzleClone, a formal framework for synthesizing verifiable data at scale using Satisfiability M…

Learning to vary: Teaching LMs to reproduce human linguistic variability in next-word prediction
Tobias Groot, Salo Lacunes, Evgenia Ilia
https://arxiv.org/abs/2509.17794 https:…

Learning to vary: Teaching LMs to reproduce human linguistic variability in next-word prediction
Natural language generation (NLG) tasks are often subject to inherent variability; \emph{e.g.} predicting the next word given a context has multiple valid responses, evident when asking multiple humans to complete the task. While having language models (LMs) that are aligned pluralistically, so that they are able to reproduce well the inherent diversity in perspectives of an entire population of interest is clearly beneficial, \citet{ilia2024predict} show that LMs do not reproduce this type of …

See&Trek: Training-Free Spatial Prompting for Multimodal Large Language Model
Pengteng Li, Pinhao Song, Wuyang Li, Weiyu Guo, Huizai Yao, Yijie Xu, Dugang Liu, Hui Xiong
https://arxiv.org/abs/2509.16087

See&Trek: Training-Free Spatial Prompting for Multimodal Large Language Model
We introduce SEE&TREK, the first training-free prompting framework tailored to enhance the spatial understanding of Multimodal Large Language Models (MLLMS) under vision-only constraints. While prior efforts have incorporated modalities like depth or point clouds to improve spatial reasoning, purely visualspatial understanding remains underexplored. SEE&TREK addresses this gap by focusing on two core principles: increasing visual diversity and motion reconstruction. For visual diversity, we con…

Dual-Phase Playtime-guided Recommendation: Interest Intensity Exploration and Multimodal Random Walks
Jingmao Zhang, Zhiting Zhao, Yunqi Lin, Jianghong Ma, Tianjun Wei, Haijun Zhang, Xiaofeng Zhang
https://arxiv.org/abs/2508.14058

Dual-Phase Playtime-guided Recommendation: Interest Intensity Exploration and Multimodal Random Walks
The explosive growth of the video game industry has created an urgent need for recommendation systems that can scale with expanding catalogs and maintain user engagement. While prior work has explored accuracy and diversity in recommendations, existing models underutilize playtime, a rich behavioral signal unique to gaming platforms, and overlook the potential of multimodal information to enhance diversity. In this paper, we propose DP2Rec, a novel Dual-Phase Playtime-guided Recommendation mode…

Dwarf diversity in $\Lambda$CDM with baryons
Akaxia Cruz, Alyson Brooks, Mariangela Lisanti, Annika H. G. Peter, Robel Geda, Thomas Quinn, Michael Tremmel, Ferah Munshi, Ben Keller, James Wadsley
https://arxiv.org/abs/2510.11800

Dwarf diversity in $Λ$CDM with baryons
Observed rotation curves of dwarf galaxies exhibit significant diversity at fixed halo mass, challenging galaxy formation within the Cold Dark Matter (CDM) model. Previous cosmological galaxy formation simulations with baryonic physics fail to reproduce the full diversity of rotation curves, suggesting either that there is a flaw in baryonic feedback models, or that an alternative to CDM must be invoked. In this work, we use the Marvelous Massive Dwarf zoom-in simulations, a suite of high-resol…

Warning that Trump scrapping diversity orders could hurt global economic growth | The Independent
https://www.independent.co.uk/news/world/americas/trump-diversity-economic-growth-women-mariella-frostrup-b2839581.html

Trump’s administration simply will not stop setting up snitch lines,
urging federal staff to rat on each other for the crime of being anti-Trump
or in favor of the virtues of diversity, equity, and inclusion.
https://www.rollingstone.com/pol…

Trump’s Government Is a Den of Snitches, ‘Freaks,’ and Paranoid Tyrants
The Department of Health and Human Services is the latest agency to ask government employees to snitch about diversity practices.

OSCAR: Orthogonal Stochastic Control for Alignment-Respecting Diversity in Flow Matching
Jingxuan Wu, Zhenglin Wan, Xingrui Yu, Yuzhe Yang, Bo An, Ivor Tsang
https://arxiv.org/abs/2510.09060

OSCAR: Orthogonal Stochastic Control for Alignment-Respecting Diversity in Flow Matching
Flow-based text-to-image models follow deterministic trajectories, forcing users to repeatedly sample to discover diverse modes, which is a costly and inefficient process. We present a training-free, inference-time control mechanism that makes the flow itself diversity-aware. Our method simultaneously encourages lateral spread among trajectories via a feature-space objective and reintroduces uncertainty through a time-scheduled stochastic perturbation. Crucially, this perturbation is projected …

DivLogicEval: A Framework for Benchmarking Logical Reasoning Evaluation in Large Language Models
Tsz Ting Chung, Lemao Liu, Mo Yu, Dit-Yan Yeung
https://arxiv.org/abs/2509.15587

DivLogicEval: A Framework for Benchmarking Logical Reasoning Evaluation in Large Language Models
Logic reasoning in natural language has been recognized as an important measure of human intelligence for Large Language Models (LLMs). Popular benchmarks may entangle multiple reasoning skills and thus provide unfaithful evaluations on the logic reasoning skill. Meanwhile, existing logic reasoning benchmarks are limited in language diversity and their distributions are deviated from the distribution of an ideal logic reasoning benchmark, which may lead to biased evaluation results. This paper …

Reading Between the Lines: A Study of Thematic Bias in Book Recommender Systems
Nityaa Kalra, Savvina Daniil
https://arxiv.org/abs/2508.15643 https://arxiv…

Reading Between the Lines: A Study of Thematic Bias in Book Recommender Systems
Recommender systems help users discover new content, but can also reinforce existing biases, leading to unfair exposure and reduced diversity. This paper introduces and investigates thematic bias in book recommendations, defined as a disproportionate favouring or neglect of certain book themes. We adopt a multi-stage bias evaluation framework using the Book-Crossing dataset to evaluate thematic bias in recommendations and its impact on different user groups. Our findings show that thematic bi…

Diversity First, Quality Later: A Two-Stage Assumption for Language Model Alignment
Zetian Sun, Dongfang Li, Baotian Hu
https://arxiv.org/abs/2508.10530 https://

Diversity First, Quality Later: A Two-Stage Assumption for Language Model Alignment
The alignment of language models (LMs) with human preferences is critical for building reliable AI systems. The problem is typically framed as optimizing an LM policy to maximize the expected reward that reflects human preferences. Recently, Direct Preference Optimization (DPO) was proposed as a LM alignment method that directly optimize the policy from static preference data, and further improved by incorporating on-policy sampling (i.e., preference candidates generated during the training loo…

Towards Robust Visual Continual Learning with Multi-Prototype Supervision
Xiwei Liu, Yulong Li, Yichen Li, Xinlin Zhuang, Haolin Yang, Huifa Li, Imran Razzak
https://arxiv.org/abs/2509.16011

Towards Robust Visual Continual Learning with Multi-Prototype Supervision
Language-guided supervision, which utilizes a frozen semantic target from a Pretrained Language Model (PLM), has emerged as a promising paradigm for visual Continual Learning (CL). However, relying on a single target introduces two critical limitations: 1) semantic ambiguity, where a polysemous category name results in conflicting visual representations, and 2) intra-class visual diversity, where a single prototype fails to capture the rich variety of visual appearances within a class. To this …

Mind the Gap: Conformative Decoding to Improve Output Diversity of Instruction-Tuned Large Language Models
Max Peeperkorn, Tom Kouwenhoven, Dan Brown, Anna Jordanous
https://arxiv.org/abs/2507.20956

Mind the Gap: Conformative Decoding to Improve Output Diversity of Instruction-Tuned Large Language Models
Instruction-tuning large language models (LLMs) reduces the diversity of their outputs, which has implications for many tasks, particularly for creative tasks. This paper investigates the ``diversity gap'' for a writing prompt narrative generation task. This gap emerges as measured by current diversity metrics for various open-weight and open-source LLMs. The results show significant decreases in diversity due to instruction-tuning. We explore the diversity loss at each fine-tuning stage for th…

ATLAS: Decoupling Skeletal and Shape Parameters for Expressive Parametric Human Modeling
Jinhyung Park, Javier Romero, Shunsuke Saito, Fabian Prada, Takaaki Shiratori, Yichen Xu, Federica Bogo, Shoou-I Yu, Kris Kitani, Rawal Khirodkar
https://arxiv.org/abs/2508.15767

ATLAS: Decoupling Skeletal and Shape Parameters for Expressive Parametric Human Modeling
Parametric body models offer expressive 3D representation of humans across a wide range of poses, shapes, and facial expressions, typically derived by learning a basis over registered 3D meshes. However, existing human mesh modeling approaches struggle to capture detailed variations across diverse body poses and shapes, largely due to limited training data diversity and restrictive modeling assumptions. Moreover, the common paradigm first optimizes the external body surface using a linear basis…

Enhancing Diversity in Large Language Models via Determinantal Point Processes
Yilei Chen, Souradip Chakraborty, Lorenz Wolf, Ioannis Ch. Paschalidis, Aldo Pacchiano
https://arxiv.org/abs/2509.04784

Enhancing Diversity in Large Language Models via Determinantal Point Processes
Supervised fine-tuning and reinforcement learning are two popular methods for post-training large language models (LLMs). While improving the model's performance on downstream tasks, they often reduce the model's output diversity, leading to narrow, canonical responses. Existing methods to enhance diversity are limited, either by operating at inference time or by focusing on lexical differences. We propose a novel training method named DQO based on determinantal point processes (DPPs) to jointl…