Tootfinder

We offer rolling admission for our online grad certificate in Digital Curation, so you can apply any time. Our spring courses will cover #DigitalPreservation #DigitalStorage #Metadata

Agent-centric learning: from external reward maximization to internal knowledge curation
Hanqi Zhou, Fryderyk Mantiuk, David G. Nagy, Charley M. Wu
https://arxiv.org/abs/2507.22255

Agent-centric learning: from external reward maximization to internal knowledge curation
The pursuit of general intelligence has traditionally centered on external objectives: an agent's control over its environments or mastery of specific tasks. This external focus, however, can produce specialized agents that lack adaptability. We propose representational empowerment, a new perspective towards a truly agent-centric learning paradigm by moving the locus of control inward. This objective measures an agent's ability to controllably maintain and diversify its own knowledge structures…

ML-Asset Management: Curation, Discovery, and Utilization
Mengying Wang, Moming Duan, Yicong Huang, Chen Li, Bingsheng He, Yinghui Wu
https://arxiv.org/abs/2509.23577 https://…

ML-Asset Management: Curation, Discovery, and Utilization
Machine learning (ML) assets, such as models, datasets, and metadata, are central to modern ML workflows. Despite their explosive growth in practice, these assets are often underutilized due to fragmented documentation, siloed storage, inconsistent licensing, and lack of unified discovery mechanisms, making ML-asset management an urgent challenge. This tutorial offers a comprehensive overview of ML-asset management activities across its lifecycle, including curation, discovery, and utilization.…

🇺🇦 #NowPlaying on KEXP's #Roadhouse
Pacific Range:
🎵 Guiding the Mast
#PacificRange
https://curation-records.bandcamp.com/track/guiding-the-mast
https://open.spotify.com/track/2LPYNcHhhQtcblPpRXRYZ7

celegans_interactomes: C. elegans interactomes (2009)
Ten networks of protein-protein interactions in Caenorhabditis elegans (nematode), from yeast two-hybrid experiments, biological process maps, literature curation, orthologous interactions, and genetic interactions. The WI8 network combines WI2004, WI2007 and BPmaps, while the Integrated Network combines data from all sources.
This network has 431 nodes and 438 edges.
Tags: Biological, Protein interactions, Unweighted

LABELING COPILOT: A Deep Research Agent for Automated Data Curation in Computer Vision
Debargha Ganguly, Sumit Kumar, Ishwar Balappanawar, Weicong Chen, Shashank Kambhatla, Srinivasan Iyengar, Shivkumar Kalyanaraman, Ponnurangam Kumaraguru, Vipin Chaudhary
https://arxiv.org/abs/2509.22631

LABELING COPILOT: A Deep Research Agent for Automated Data Curation in Computer Vision
Curating high-quality, domain-specific datasets is a major bottleneck for deploying robust vision systems, requiring complex trade-offs between data quality, diversity, and cost when researching vast, unlabeled data lakes. We introduce Labeling Copilot, the first data curation deep research agent for computer vision. A central orchestrator agent, powered by a large multimodal language model, uses multi-step reasoning to execute specialized tools across three core capabilities: (1) Calibrated Di…

«The recent news concerning GigaScience’s owners, BGI, laying off the entire editorial, software and curation team in Hong Kong on short notice, has filled us with both surprise and deep disappointment.»
Indeed, GigaScience has always been a mainstay at BOSC and the larger intersection of life sciences & open source/science & citizen science.
https://www.open-bio.org/2025/09/30/2025-09-30-gigascience/

Crosslisted article(s) found for cs.AI. https://arxiv.org/list/cs.AI/new
[12/21]:
- Efficient Multi-turn RL for GUI Agents via Decoupled Training and Adaptive Data Curation
Li, Hu, Shang, Wu, Liu, Liu, Gao, Shi, Zhang, Zhang, Shi, YU, Wu, Wu, Jia, Xiang, He, Li

Deconstructing Self-Bias in LLM-generated Translation Benchmarks
Wenda Xu, Sweta Agrawal, Vil\'em Zouhar, Markus Freitag, Daniel Deutsch
https://arxiv.org/abs/2509.26600 htt…

Deconstructing Self-Bias in LLM-generated Translation Benchmarks
As large language models (LLMs) begin to saturate existing benchmarks, automated benchmark creation using LLMs (LLM as a benchmark) has emerged as a scalable alternative to slow and costly human curation. While these generated test sets have to potential to cheaply rank models, we demonstrate a critical flaw. LLM generated benchmarks systematically favor the model that created the benchmark, they exhibit self bias on low resource languages to English translation tasks. We show three key finding…

CodableLLM: Automating Decompiled and Source Code Mapping for LLM Dataset Generation
Dylan Manuel, Paul Rad
https://arxiv.org/abs/2507.22066 https://arxiv.…

CodableLLM: Automating Decompiled and Source Code Mapping for LLM Dataset Generation
The generation of large, high-quality datasets for code understanding and generation remains a significant challenge, particularly when aligning decompiled binaries with their original source code. To address this, we present CodableLLM, a Python framework designed to automate the creation and curation of datasets by mapping decompiled functions to their corresponding source functions. This process enhances the alignment between decompiled and source code representations, facilitating the devel…

"Caring for Data’s Soul: The development of a Curation Impact Factor to pinpoint the effects of data curation activities on data quality" https://doi.org/10.2218/ijdc.v19i1.1030

Burst: Collaborative Curation in Connected Social Media Communities
Yutong Zhang, Taeuk Kang, Sydney Yeh, Anavi Baddepudi, Lindsay Popowski, Tiziano Piccardi, Michael S. Bernstein
https://arxiv.org/abs/2508.19768

Burst: Collaborative Curation in Connected Social Media Communities
Positive social interactions can occur in groups of many shapes and sizes, spanning from small and private to large and open. However, social media tends to binarize our experiences into either isolated small groups or into large public squares. In this paper, we introduce Burst, a social media design that allows users to share and curate content between many spaces of varied size and composition. Users initially post content to small trusted groups, who can then burst that content, routing it …

Middo: Model-Informed Dynamic Data Optimization for Enhanced LLM Fine-Tuning via Closed-Loop Learning
Zinan Tang, Xin Gao, Qizhi Pei, Zhuoshi Pan, Mengzhang Cai, Jiang Wu, Conghui He, Lijun Wu
https://arxiv.org/abs/2508.21589

Middo: Model-Informed Dynamic Data Optimization for Enhanced LLM Fine-Tuning via Closed-Loop Learning
Supervised Fine-Tuning (SFT) Large Language Models (LLM) fundamentally rely on high-quality training data. While data selection and data synthesis are two common strategies to improve data quality, existing approaches often face limitations in static dataset curation that fail to adapt to evolving model capabilities. In this paper, we introduce Middo, a self-evolving Model-informed dynamic data optimization framework that uses model-aware data selection and context-preserving data refinement. U…

Experiversum: an Ecosystem for Curating and Enhancing Data-Driven Experimental Science
Genoveva Vargas-Solar (LIRIS), Umberto Costa (ERIC, UL2), J\'er\^ome Darmont (ERIC, UL2), Javier Espinosa-Oviedo (ERIC, UCBL), Carmem Hara (ERIC, UL2), Sabine Loudcher (ERIC, UL2), Regina Motz, Martin A. Musicante, Jos\'e-Luis Zechinelli-Martini
https://

Experiversum: an Ecosystem for Curating and Enhancing Data-Driven Experimental Science
This paper introduces Experiversum, a lakehouse-based ecosystem that supports the curation, documentation and reproducibility of exploratory experiments. Experiversum enables structured research through iterative data cycles, while capturing metadata and collaborative decisions. Demonstrated through case studies in Earth, Life and Political Sciences, Experiversum promotes transparent workflows and multi-perspective result interpretation. Experiversum bridges exploratory and reproducible researc…

SMECS: A Software Metadata Extraction and Curation Software
Stephan Ferenz, Aida Jafarbigloo, Oliver Werth, Astrid Nie{\ss}e
https://arxiv.org/abs/2507.18159 https://

SMECS: A Software Metadata Extraction and Curation Software
Metadata play a crucial role in adopting the FAIR principles for research software and enables findability and reusability. However, creating high-quality metadata can be resource-intensive for researchers and research software engineers. To address this challenge, we developed the Software Metadata Extraction and Curation Software (SMECS) which integrates the extraction of metadata from existing sources together with a user-friendly interface for metadata curation. SMECS extracts metadata from…

OpenGVL - Benchmarking Visual Temporal Progress for Data Curation
Pawe{\l} Budzianowski, Emilia Wi\'snios, Gracjan G\'oral, Igor Kulakov, Viktor Petrenko, Krzysztof Walas
https://arxiv.org/abs/2509.17321

OpenGVL - Benchmarking Visual Temporal Progress for Data Curation
Data scarcity remains one of the most limiting factors in driving progress in robotics. However, the amount of available robotics data in the wild is growing exponentially, creating new opportunities for large-scale data utilization. Reliable temporal task completion prediction could help automatically annotate and curate this data at scale. The Generative Value Learning (GVL) approach was recently proposed, leveraging the knowledge embedded in vision-language models (VLMs) to predict task prog…

MetaCLIP 2: A Worldwide Scaling Recipe
Yung-Sung Chuang, Yang Li, Dong Wang, Ching-Feng Yeh, Kehan Lyu, Ramya Raghavendra, James Glass, Lifei Huang, Jason Weston, Luke Zettlemoyer, Xinlei Chen, Zhuang Liu, Saining Xie, Wen-tau Yih, Shang-Wen Li, Hu Xu
https://arxiv.org/abs/2507.22062

MetaCLIP 2: A Worldwide Scaling Recipe
Contrastive Language-Image Pretraining (CLIP) is a popular foundation model, supporting from zero-shot classification, retrieval to encoders for multimodal large language models (MLLMs). Although CLIP is successfully trained on billion-scale image-text pairs from the English world, scaling CLIP's training further to learning from the worldwide web data is still challenging: (1) no curation method is available to handle data points from non-English world; (2) the English performance from existin…

OLMoASR: Open Models and Data for Training Robust Speech Recognition Models
Huong Ngo, Matt Deitke, Martijn Bartelds, Sarah Pratt, Josh Gardner, Matt Jordan, Ludwig Schmidt
https://arxiv.org/abs/2508.20869

OLMoASR: Open Models and Data for Training Robust Speech Recognition Models
Improvements in training data scale and quality have led to significant advances, yet its influence in speech recognition remains underexplored. In this paper, we present a large-scale dataset, OLMoASR-Pool, and series of models, OLMoASR, to study and develop robust zero-shot speech recognition models. Beginning from OLMoASR-Pool, a collection of 3M hours of English audio and 17M transcripts, we design text heuristic filters to remove low-quality or mistranscribed data. Our curation pipeline pr…

CaTE Data Curation for Trustworthy AI
Mary Versa Clemens-Sewall, Christopher Cervantes, Emma Rafkin, J. Neil Otte, Tom Magelinski, Libby Lewis, Michelle Liu, Dana Udwin, Monique Kirkman-Bey
https://arxiv.org/abs/2508.14741

CaTE Data Curation for Trustworthy AI
This report provides practical guidance to teams designing or developing AI-enabled systems for how to promote trustworthiness during the data curation phase of development. In this report, the authors first define data, the data curation phase, and trustworthiness. We then describe a series of steps that the development team, especially data scientists, can take to build a trustworthy AI-enabled system. We enumerate the sequence of core steps and trace parallel paths where alternatives exist. …

Need to put your collection in a database and get it online? This fall UMaine's offering Digital Collections and Exhibitions (DIG 540) online with Craig Dietrich.
#Archives

Medium's CEO explains how the platform's AI policy has evolved as it adopts some AI tools while prioritizing human curation and inviting community feedback (Tony Stubblebine/The Medium Blog)
https://medium.com/blog/we-want-your-f

We want your feedback: How can writers use AI to tell human stories?
How we are navigating the role AI does and doesn’t play in our mission to deepen understanding.

Culling Misinformation from Gen AI: Toward Ethical Curation and Refinement
Prerana Khatiwada, Grace Donaher, Jasymyn Navarro, Lokesh Bhatta
https://arxiv.org/abs/2507.14242

Culling Misinformation from Gen AI: Toward Ethical Curation and Refinement
While Artificial Intelligence (AI) is not a new field, recent developments, especially with the release of generative tools like ChatGPT, have brought it to the forefront of the minds of industry workers and academic folk alike. There is currently much talk about AI and its ability to reshape many everyday processes as we know them through automation. It also allows users to expand their ideas by suggesting things they may not have thought of on their own and provides easier access to informati…

White House officials said they would review the Smithsonian’s exhibition text, curation, exhibition planning and collections,
starting with eight museums
“The Smithsonian’s work is grounded in a deep commitment to scholarly excellence, rigorous research, and the accurate, factual presentation of history,”
a Smithsonian spokesperson said in a statement Tuesday afternoon.
“We are reviewing the letter with this commitment in mind and will continue to collaborate constr…

White House announces more aggressive review of Smithsonian museums
In a letter to the Smithsonian’s leader, White House officials said they would review exhibition text, curation, exhibition planning and collections starting with eight museums.

Medium's CEO explains how the platform's AI policy has evolved as it adopts some AI tools while prioritizing human curation and seeking community feedback (Tony Stubblebine/The Medium Blog)
https://medium.com/blog/we-want-your-f…

We want your feedback: How can writers use AI to tell human stories?
How we are navigating the role AI does and doesn’t play in our mission to deepen understanding.

'I used to think curation was something done to us, a middle-class job where someone with elbow patches picks which version of our past is respectable enough to put behind glass' 🔥
From ‘Keep The Flame Burning’: What Happens When You Hand the Archives to the People They Forgot About

Lean Meets Theoretical Computer Science: Scalable Synthesis of Theorem Proving Challenges in Formal-Informal Pairs
Terry Jingchen Zhang, Wenyuan Jiang, Rongchuan Liu, Yisong Wang, Junran Yang, Ning Wang, Nicole Ni, Yinya Huang, Mrinmaya Sachan
https://arxiv.org/abs/2508.15878

Lean Meets Theoretical Computer Science: Scalable Synthesis of Theorem Proving Challenges in Formal-Informal Pairs
Formal theorem proving (FTP) has emerged as a critical foundation for evaluating the reasoning capabilities of large language models, enabling automated verification of mathematical proofs at scale. However, progress has been constrained by limited datasets due to the high cost of manual curation and the scarcity of challenging problems with verified formal-informal correspondences. We propose leveraging theoretical computer science (TCS) as a scalable source of rigorous proof problems, where a…

Cascade! Human in the loop shortcomings can increase the risk of failures in recommender systems
Wm. Matthew Kennedy, Nishanshi Shukla, Cigdem Patlak, Blake Chambers, Theodora Skeadas, Tuesday, Kingsley Owadara, Aayush Dhanotiya
https://arxiv.org/abs/2509.20099

Cascade! Human in the loop shortcomings can increase the risk of failures in recommender systems
Recommender systems are among the most commonly deployed systems today. Systems design approaches to AI-powered recommender systems have done well to urge recommender system developers to follow more intentional data collection, curation, and management procedures. So too has the "human-in-the-loop" paradigm been widely adopted, primarily to address the issue of accountability. However, in this paper, we take the position that human oversight in recommender system design also entails novel risk…

Bayesian Anomaly Detection for Ia Cosmology: Automating SALT3 Data Curation
S. A. K. Leeney, W. J. Handley, H. T. J. Bevins, E. de Lera Acedo
https://arxiv.org/abs/2509.13394 ht…

Bayesian Anomaly Detection for Ia Cosmology: Automating SALT3 Data Curation
Precision cosmology with Type Ia supernovae (SNe Ia) requires robust quality control of large, heterogeneous datasets. Current data processing often relies on manual, subjective rejection of photometric data, a practice that is not scalable for forthcoming surveys like the Vera C. Rubin Observatory's Legacy Survey of Space and Time (LSST). We present a Bayesian framework that automates this step by integrating anomaly detection directly into the light curve fitting process. While the framework …

Identifying Constructive Conflict in Online Discussions through Controversial yet Toxicity Resilient Posts
Ozgur Can Seckin, Bao Tran Truong, Alessandro Flammini, Filippo Menczer
https://arxiv.org/abs/2509.18303

Herewith yet another curation of Long Links: https://www.tbray.org/ongoing/When/202x/2025/08/04/Long-Links
This month featuring new music from the New Eves, Coureurs des Bois, assembly mutation testing, and more flirting with Class Reductionism and Late Ca…

Feel like your collection website could be better but don't know the necessary tools? A few seats left in UMaine's online course in Digital Collections and Exhibitions starting 3 Sep, which teaches  the fundamentals of getting your records in a database and putting them online https://DigitalCuration.UMaine.edu

celegans_interactomes: C. elegans interactomes (2009)
Ten networks of protein-protein interactions in Caenorhabditis elegans (nematode), from yeast two-hybrid experiments, biological process maps, literature curation, orthologous interactions, and genetic interactions. The WI8 network combines WI2004, WI2007 and BPmaps, while the Integrated Network combines data from all sources.
This network has 431 nodes and 438 edges.
Tags: Biological, Protein interactions, Unweighted

"Development of an Integrated Lifecycle of #RDM #Tools: Looking Back and Forward at KU Leuven"
https://ijdc.net/index.…

Mining the Long Tail: A Comparative Study of Data-Centric Criticality Metrics for Robust Offline Reinforcement Learning in Autonomous Motion Planning
Antonio Guillen-Perez
https://arxiv.org/abs/2508.18397

Mining the Long Tail: A Comparative Study of Data-Centric Criticality Metrics for Robust Offline Reinforcement Learning in Autonomous Motion Planning
Offline Reinforcement Learning (RL) presents a promising paradigm for training autonomous vehicle (AV) planning policies from large-scale, real-world driving logs. However, the extreme data imbalance in these logs, where mundane scenarios vastly outnumber rare "long-tail" events, leads to brittle and unsafe policies when using standard uniform data sampling. In this work, we address this challenge through a systematic, large-scale comparative study of data curation strategies designed to focus …

Improving Deep Learning for Accelerated MRI With Data Filtering
Kang Lin, Anselm Krainovic, Kun Wang, Reinhard Heckel
https://arxiv.org/abs/2508.13822 https://

Improving Deep Learning for Accelerated MRI With Data Filtering
Deep neural networks achieve state-of-the-art results for accelerated MRI reconstruction. Most research on deep learning based imaging focuses on improving neural network architectures trained and evaluated on fixed and homogeneous training and evaluation data. In this work, we investigate data curation strategies for improving MRI reconstruction. We assemble a large dataset of raw k-space data from 18 public sources consisting of 1.1M images and construct a diverse evaluation set comprising 48…

Building Data-Driven Occupation Taxonomies: A Bottom-Up Multi-Stage Approach via Semantic Clustering and Multi-Agent Collaboration
Nan Li, Bo Kang, Tijl De Bie
https://arxiv.org/abs/2509.15786

Building Data-Driven Occupation Taxonomies: A Bottom-Up Multi-Stage Approach via Semantic Clustering and Multi-Agent Collaboration
Creating robust occupation taxonomies, vital for applications ranging from job recommendation to labor market intelligence, is challenging. Manual curation is slow, while existing automated methods are either not adaptive to dynamic regional markets (top-down) or struggle to build coherent hierarchies from noisy data (bottom-up). We introduce CLIMB (CLusterIng-based Multi-agent taxonomy Builder), a framework that fully automates the creation of high-quality, data-driven taxonomies from raw job …

Best Practices and Considerations for Child Speech Corpus Collection and Curation in Educational, Clinical, and Forensic Scenarios
John Hansen, Satwik Dutta, Ellen Grand
https://arxiv.org/abs/2507.12870

Best Practices and Considerations for Child Speech Corpus Collection and Curation in Educational, Clinical, and Forensic Scenarios
A child's spoken ability continues to change until their adult age. Until 7-8yrs, their speech sound development and language structure evolve rapidly. This dynamic shift in their spoken communication skills and data privacy make it challenging to curate technology-ready speech corpora for children. This study aims to bridge this gap and provide researchers and practitioners with the best practices and considerations for developing such a corpus based on an intended goal. Although primarily foc…

@… I do like the thought.
I think that curation needs curators who curate …

PHP turned 30 last month. Why does this language that powers 75% of the web—including Facebook, Wikipedia, and WordPress—have such staying power? Find out by registering for this fall's DIG 540, UMaine's online course in building cultural databases.
https://DigitalCuration.UMaine.edu

Crosslisted article(s) found for astro-ph.CO. https://arxiv.org/list/astro-ph.CO/new
[1/1]:
- Bayesian Anomaly Detection for Ia Cosmology: Automating SALT3 Data Curation
S. A. K. Leeney, W. J. Handley, H. T. J. Bevins, E. de Lera Acedo

HypoGeneAgent: A Hypothesis Language Agent for Gene-Set Cluster Resolution Selection Using Perturb-seq Datasets
Ying Yuan, Xing-Yue Monica Ge, Aaron Archer Waterman, Tommaso Biancalani, David Richmond, Yogesh Pandit, Avtar Singh, Russell Littman, Jin Liu, Jan-Christian Huetter, Vladimir Ermakov
https://arxiv.org/abs/2509.09740

HypoGeneAgent: A Hypothesis Language Agent for Gene-Set Cluster Resolution Selection Using Perturb-seq Datasets
Large-scale single-cell and Perturb-seq investigations routinely involve clustering cells and subsequently annotating each cluster with Gene-Ontology (GO) terms to elucidate the underlying biological programs. However, both stages, resolution selection and functional annotation, are inherently subjective, relying on heuristics and expert curation. We present HYPOGENEAGENT, a large language model (LLM)-driven framework, transforming cluster annotation into a quantitatively optimizable task. Init…

🇺🇦 #NowPlaying on #BBC6Music's #RileyAndCoe
Joe Harvey-Whyte And Bobby Lee:
🎵 Smoke Signals
#JoeHarveyWhyteAndBobbyLee
https://curation-records.bandcamp.com/track/smoke-signals
https://open.spotify.com/track/3W44JcdMkH5or7IJr7Y5Bp

zERExtractor:An Automated Platform for Enzyme-Catalyzed Reaction Data Extraction from Scientific Literature
Rui Zhou, Haohui Ma, Tianle Xin, Lixin Zou, Qiuyue Hu, Hongxi Cheng, Mingzhi Lin, Jingjing Guo, Sheng Wang, Guoqing Zhang, Yanjie Wei, Liangzhen Zheng
https://arxiv.org/abs/2508.09995

zERExtractor:An Automated Platform for Enzyme-Catalyzed Reaction Data Extraction from Scientific Literature
The rapid expansion of enzyme kinetics literature has outpaced the curation capabilities of major biochemical databases, creating a substantial barrier to AI-driven modeling and knowledge discovery. We present zERExtractor, an automated and extensible platform for comprehensive extraction of enzyme-catalyzed reaction and activity data from scientific literature. zERExtractor features a unified, modular architecture that supports plug-and-play integration of state-of-the-art models, including la…

celegans_interactomes: C. elegans interactomes (2009)
Ten networks of protein-protein interactions in Caenorhabditis elegans (nematode), from yeast two-hybrid experiments, biological process maps, literature curation, orthologous interactions, and genetic interactions. The WI8 network combines WI2004, WI2007 and BPmaps, while the Integrated Network combines data from all sources.
This network has 2436 nodes and 136930 edges.
Tags: Biological, Protein interactions, Unweighte…

Replaced article(s) found for eess.AS. https://arxiv.org/list/eess.AS/new
[1/1]:
- Less is More: Data Curation Matters in Scaling Speech Enhancement
Li, Zhang, Wang, Scheibler, Saijo, Cornell, Fu, Sach, Ni, Kumar, Fingscheidt, Watanabe, Qian

SafetyFlow: An Agent-Flow System for Automated LLM Safety Benchmarking
Xiangyang Zhu, Yuan Tian, Chunyi Li, Kaiwei Zhang, Wei Sun, Guangtao Zhai
https://arxiv.org/abs/2508.15526

SafetyFlow: An Agent-Flow System for Automated LLM Safety Benchmarking
The rapid proliferation of large language models (LLMs) has intensified the requirement for reliable safety evaluation to uncover model vulnerabilities. To this end, numerous LLM safety evaluation benchmarks are proposed. However, existing benchmarks generally rely on labor-intensive manual curation, which causes excessive time and resource consumption. They also exhibit significant redundancy and limited difficulty. To alleviate these problems, we introduce SafetyFlow, the first agent-flow sys…

Beyond Policy Optimization: A Data Curation Flywheel for Sparse-Reward Long-Horizon Planning
Yutong Wang, Pengliang Ji, Kaixin Li, Baolong Bi, Tao Feng, Guillaume Sartoretti
https://arxiv.org/abs/2508.03018

Beyond Policy Optimization: A Data Curation Flywheel for Sparse-Reward Long-Horizon Planning
Large Language Reasoning Models have demonstrated remarkable success on static tasks, yet their application to multi-round agentic planning in interactive environments faces two fundamental challenges. First, the intractable credit assignment problem renders conventional reinforcement learning ineffective in sparse-reward settings. Second, the computational overhead of verbose, step-by-step reasoning histories is prohibitive. To address these challenges, we propose BPO, a three-stage framework …

Improving the FAIRness and Sustainability of the NHGRI Resources Ecosystem
Larry Babb, Carol Bult, Vincent J. Carey, Robert J. Carroll, Benjamin C. Hitz, Chris J. Mungall, Heidi L. Rehm, Michael C. Schatz, Alex Wagner, NHGRI Resource Workshop Community
https://arxiv.org/abs/2508.13498

Improving the FAIRness and Sustainability of the NHGRI Resources Ecosystem
In 2024, NHGRI-funded genomic resource projects completed a Self-Assessment Tool (SAT) and interviews to evaluate their application of FAIR (Findable, Accessible, Interoperable, Reusable) principles and sustainability. Key challenges were identified in metadata tools, data curation, variant identifiers, and data processing. Addressing these needs, we engaged the community through webinars and discussions, leading to a two-day workshop in March 2025. The workshop developed targeted recommendatio…

Applying the Chinese Wall Reverse Engineering Technique to Large Language Model Code Editing
Manatsawin Hanmongkolchai
https://arxiv.org/abs/2507.15599 htt…

Applying the Chinese Wall Reverse Engineering Technique to Large Language Model Code Editing
Large language models for code (Code LLM) are increasingly utilized in programming environments. Despite their utility, the training datasets for top LLM remain undisclosed, raising concerns about potential copyright violations. Some models, such as Pleias and Comma put emphasis on data curation and licenses, however, with limited training data these models are not competitive and only serve as proof of concepts. To improve the utility of these models, we propose an application of the "Chinese …

SAIL-VL2 Technical Report
Weijie Yin, Yongjie Ye, Fangxun Shu, Yue Liao, Zijian Kang, Hongyuan Dong, Haiyang Yu, Dingkang Yang, Jiacong Wang, Han Wang, Wenzhuo Liu, Xiao Liang, Shuicheng Yan, Chao Feng
https://arxiv.org/abs/2509.14033

SAIL-VL2 Technical Report
We introduce SAIL-VL2, an open-suite vision-language foundation model (LVM) for comprehensive multimodal understanding and reasoning. As the successor to SAIL-VL, SAIL-VL2 achieves state-of-the-art performance at the 2B and 8B parameter scales across diverse image and video benchmarks, demonstrating strong capabilities from fine-grained perception to complex reasoning. Three core innovations drive its effectiveness. First, a large-scale data curation pipeline with scoring and filtering strategi…

An HTR-LLM Workflow for High-Accuracy Transcription and Analysis of Abbreviated Latin Court Hand
Joshua D. Isom
https://arxiv.org/abs/2507.04132 https://…

An HTR-LLM Workflow for High-Accuracy Transcription and Analysis of Abbreviated Latin Court Hand
This article presents and validates an ideal, four-stage workflow for the high-accuracy transcription and analysis of challenging medieval legal documents. The process begins with a specialized Handwritten Text Recognition (HTR) model, itself created using a novel "Clean Ground Truth" curation method where a Large Language Model (LLM) refines the training data. This HTR model provides a robust baseline transcription (Stage 1). In Stage 2, this baseline is fed, along with the original document i…

celegans_interactomes: C. elegans interactomes (2009)
Ten networks of protein-protein interactions in Caenorhabditis elegans (nematode), from yeast two-hybrid experiments, biological process maps, literature curation, orthologous interactions, and genetic interactions. The WI8 network combines WI2004, WI2007 and BPmaps, while the Integrated Network combines data from all sources.
This network has 1496 nodes and 1816 edges.
Tags: Biological, Protein interactions, Unweighted

Will AI rescue cultural heritage or replace it? In this IEEE video, learn how LLMs act as a compression algorithm for the Internet, enabling new forms of access while simultaneously threatening to replace ground truth with convincing facsimiles.
I also explain why mechanistic analogies, unlike animate metaphors like a child or parrot, can help us tune AI to get optimal results.

Online Homogeneity Can Emerge Without Filtering Algorithms or Homophily Preferences
Petter T\"ornberg
https://arxiv.org/abs/2508.10466 https://arxiv.o…

Online Homogeneity Can Emerge Without Filtering Algorithms or Homophily Preferences
Ideologically homogeneous online environments - often described as "echo chambers" or "filter bubbles" - are widely seen as drivers of polarization, radicalization, and misinformation. A central debate asks whether such homophily stems primarily from algorithmic curation or users' preference for like-minded peers. This study challenges that view by showing that homogeneity can emerge in the absence of both filtering algorithms and user preferences. Using an agent-based model inspired by Schelli…

🇺🇦 #NowPlaying on #BBC6Music's #RileyAndCoe
Joe Harvey-Whyte And Bobby Lee:
🎵 Smoke Signals
#JoeHarveyWhyteAndBobbyLee
https://curation-records.bandcamp.com/track/smoke-signals
https://open.spotify.com/track/3W44JcdMkH5or7IJr7Y5Bp

RepoForge: Training a SOTA Fast-thinking SWE Agent with an End-to-End Data Curation Pipeline Synergizing SFT and RL at Scale
Zhilong Chen, Chengzong Zhao, Boyuan Chen, Dayi Lin, Yihao Chen, Arthur Leung, Gopi Krishnan Rajbahadur, Gustavo A. Oliva, Ahmed E. Hassan
https://arxiv.org/abs/2508.01550

RepoForge: Training a SOTA Fast-thinking SWE Agent with an End-to-End Data Curation Pipeline Synergizing SFT and RL at Scale
Training software engineering (SWE) LLMs is bottlenecked by expensive infrastructure, inefficient evaluation pipelines, scarce training data, and costly quality control. We present RepoForge, an autonomous, end-to-end pipeline that generates, evaluates, and trains SWE agents at scale. Our key contributions include: (1) RepoForge-8B-Agent, achieving 17.4\% on SWE-Bench-Verified~\citep{swebench_verified2024}, establishing new state-of-the-art for $\leq$8B non-thinking LLMs; (2) 7,304 executable e…

celegans_interactomes: C. elegans interactomes (2009)
Ten networks of protein-protein interactions in Caenorhabditis elegans (nematode), from yeast two-hybrid experiments, biological process maps, literature curation, orthologous interactions, and genetic interactions. The WI8 network combines WI2004, WI2007 and BPmaps, while the Integrated Network combines data from all sources.
This network has 912 nodes and 22738 edges.
Tags: Biological, Protein interactions, Unweighted

Campaigning through the lens of Google: A large-scale algorithm audit of Google searches in the run-up to the Swiss Federal Elections 2023
Tobias Rohrbach, Mykola Makhortykh, Maryna Sydorova
https://arxiv.org/abs/2507.06018

Campaigning through the lens of Google: A large-scale algorithm audit of Google searches in the run-up to the Swiss Federal Elections 2023
Search engines like Google have become major sources of information for voters during election campaigns. To assess potential biases across candidates' gender and partisan identities in the algorithmic curation of candidate information, we conducted a large-scale algorithm audit analyzing Google's selection and ranking of information about candidates for the 2023 Swiss Federal Elections, three and one week before the election day. Results indicate that text searches prioritize media sources in …

Towards Reliable Multi-Agent Systems for Marketing Applications via Reflection, Memory, and Planning
Lorenzo Jaime Yu Flores, Junyi Shen, Xiaoyuan Gu
https://arxiv.org/abs/2508.11120

Towards Reliable Multi-Agent Systems for Marketing Applications via Reflection, Memory, and Planning
Recent advances in large language models (LLMs) enabled the development of AI agents that can plan and interact with tools to complete complex tasks. However, literature on their reliability in real-world applications remains limited. In this paper, we introduce a multi-agent framework for a marketing task: audience curation. To solve this, we introduce a framework called RAMP that iteratively plans, calls tools, verifies the output, and generates suggestions to improve the quality of the audie…

Replaced article(s) found for cs.LG. https://arxiv.org/list/cs.LG/new
[4/5]:
- SCIZOR: A Self-Supervised Approach to Data Curation for Large-Scale Imitation Learning
Yu Zhang, Yuqi Xie, Huihan Liu, Rutav Shah, Michael Wan, Linxi Fan, Yuke Zhu

Facilitating Personalized TTS for Dysarthric Speakers Using Knowledge Anchoring and Curriculum Learning
Yejin Jeon, Solee Im, Youngjae Kim, Gary Geunbae Lee
https://arxiv.org/abs/2508.10412

Facilitating Personalized TTS for Dysarthric Speakers Using Knowledge Anchoring and Curriculum Learning
Dysarthric speakers experience substantial communication challenges due to impaired motor control of the speech apparatus, which leads to reduced speech intelligibility. This creates significant obstacles in dataset curation since actual recording of long, articulate sentences for the objective of training personalized TTS models becomes infeasible. Thus, the limited availability of audio data, in addition to the articulation errors that are present within the audio, complicates personalized sp…

When Kids Mode Isn't For Kids: Investigating TikTok's "Under 13 Experience"
Olivia Figueira, Pranathi Chamarthi, Tu Le, Athina Markopoulou
https://arxiv.org/abs/2507.00299

When Kids Mode Isn't For Kids: Investigating TikTok's "Under 13 Experience"
TikTok, the social media platform that is popular among children and adolescents, offers a more restrictive "Under 13 Experience" exclusively for young users in the US, also known as TikTok's "Kids Mode". While prior research has studied various aspects of TikTok's regular mode, including privacy and personalization, TikTok's Kids Mode remains understudied, and there is a lack of transparency regarding its content curation and its safety and privacy protections for children. In this paper, (i) …

celegans_interactomes: C. elegans interactomes (2009)
Ten networks of protein-protein interactions in Caenorhabditis elegans (nematode), from yeast two-hybrid experiments, biological process maps, literature curation, orthologous interactions, and genetic interactions. The WI8 network combines WI2004, WI2007 and BPmaps, while the Integrated Network combines data from all sources.
This network has 759 nodes and 1593 edges.
Tags: Biological, Protein interactions, Unweighted…

BOOST: Out-of-Distribution-Informed Adaptive Sampling for Bias Mitigation in Stylistic Convolutional Neural Networks
Mridula Vijendran, Shuang Chen, Jingjing Deng, Hubert P. H. Shum
https://arxiv.org/abs/2507.07134

BOOST: Out-of-Distribution-Informed Adaptive Sampling for Bias Mitigation in Stylistic Convolutional Neural Networks
The pervasive issue of bias in AI presents a significant challenge to painting classification, and is getting more serious as these systems become increasingly integrated into tasks like art curation and restoration. Biases, often arising from imbalanced datasets where certain artistic styles dominate, compromise the fairness and accuracy of model predictions, i.e., classifiers are less accurate on rarely seen paintings. While prior research has made strides in improving classification performa…

Martian World Models: Controllable Video Synthesis with Physically Accurate 3D Reconstructions
Longfei Li, Zhiwen Fan, Wenyan Cong, Xinhang Liu, Yuyang Yin, Matt Foutter, Panwang Pan, Chenyu You, Yue Wang, Zhangyang Wang, Yao Zhao, Marco Pavone, Yunchao Wei
https://arxiv.org/abs/2507.07978…

Martian World Models: Controllable Video Synthesis with Physically Accurate 3D Reconstructions
Synthesizing realistic Martian landscape videos is crucial for mission rehearsal and robotic simulation. However, this task poses unique challenges due to the scarcity of high-quality Martian data and the significant domain gap between Martian and terrestrial imagery. To address these challenges, we propose a holistic solution composed of two key components: 1) A data curation pipeline Multimodal Mars Synthesis (M3arsSynth), which reconstructs 3D Martian environments from real stereo navigation…

CodeAssistBench (CAB): Dataset & Benchmarking for Multi-turn Chat-Based Code Assistance
Myeongsoo Kim, Shweta Garg, Baishakhi Ray, Varun Kumar, Anoop Deoras
https://arxiv.org/abs/2507.10646

CodeAssistBench (CAB): Dataset & Benchmarking for Multi-turn Chat-Based Code Assistance
Programming assistants powered by large language models have transformed software development, yet most benchmarks focus narrowly on code generation tasks. Recent efforts like InfiBench and StackEval attempt to address this gap using Stack Overflow data but remain limited to single-turn interactions in isolated contexts, require significant manual curation, and fail to represent complete project environments. We introduce CodeAssistBench (CAB), the first benchmark framework for evaluating multi…

celegans_interactomes: C. elegans interactomes (2009)
Ten networks of protein-protein interactions in Caenorhabditis elegans (nematode), from yeast two-hybrid experiments, biological process maps, literature curation, orthologous interactions, and genetic interactions. The WI8 network combines WI2004, WI2007 and BPmaps, while the Integrated Network combines data from all sources.
This network has 759 nodes and 1593 edges.
Tags: Biological, Protein interactions, Unweighted…

🇺🇦 #NowPlaying on KEXP's #Roadhouse
Joe Harvey-Whyte & Bobby Lee:
🎵 Flatbed Alfalfa Run To Pueblo, Colorado, Fall 1972
#JoeHarveyWhyte #BobbyLee
https://curation-records.bandcamp.com/track/flatbed-alfalfa-run-to-pueblo-colorado-fall-1972
https://open.spotify.com/track/1Dha5E7nCLgGmYXXGHK0Mv

SynGen-Vision: Synthetic Data Generation for training industrial vision models
Alpana Dubey, Suma Mani Kuriakose, Nitish Bhardwaj
https://arxiv.org/abs/2509.04894 https://

SynGen-Vision: Synthetic Data Generation for training industrial vision models
We propose an approach to generate synthetic data to train computer vision (CV) models for industrial wear and tear detection. Wear and tear detection is an important CV problem for predictive maintenance tasks in any industry. However, data curation for training such models is expensive and time-consuming due to the unavailability of datasets for different wear and tear scenarios. Our approach employs a vision language model along with a 3D simulation and rendering engine to generate synthetic…

Wearable Music2Emotion : Assessing Emotions Induced by AI-Generated Music through Portable EEG-fNIRS Fusion
Sha Zhao, Song Yi, Yangxuan Zhou, Jiadong Pan, Jiquan Wang, Jie Xia, Shijian Li, Shurong Dong, Gang Pan
https://arxiv.org/abs/2508.04723

Wearable Music2Emotion : Assessing Emotions Induced by AI-Generated Music through Portable EEG-fNIRS Fusion
Emotions critically influence mental health, driving interest in music-based affective computing via neurophysiological signals with Brain-computer Interface techniques. While prior studies leverage music's accessibility for emotion induction, three key limitations persist: \textbf{(1) Stimulus Constraints}: Music stimuli are confined to small corpora due to copyright and curation costs, with selection biases from heuristic emotion-music mappings that ignore individual affective profiles. \text…