Tootfinder

Japanese memory chipmaker Kioxia's stock falls 14% after a Bain Capital-backed entity sold $2.1B worth of shares at a discount, stoking AI valuation concerns (Bloomberg)
https://www.bloomberg.com/news/articles/2025-11-26…

Chipmaker Kioxia Sinks After Bain-Backed Firm Discloses Selloff
Kioxia Holdings Corp.’s shares dived more than 14% after a Bain Capital-backed entity unloaded $2.1 billion of shares in the Japanese memory chipmaker at a discount, stoking concerns about the lofty valuations of global AI-related firms.

Mah\={a}n\={a}ma: A Unique Testbed for Literary Entity Discovery and Linking
Sujoy Sarkar, Gourav Sarkar, Manoj Balaji Jagadeeshan, Jivnesh Sandhan, Amrith Krishna, Pawan Goyal
https://arxiv.org/abs/2509.19844

Mahānāma: A Unique Testbed for Literary Entity Discovery and Linking
High lexical variation, ambiguous references, and long-range dependencies make entity resolution in literary texts particularly challenging. We present Mahānāma, the first large-scale dataset for end-to-end Entity Discovery and Linking (EDL) in Sanskrit, a morphologically rich and under-resourced language. Derived from the Mahābhārata, the world's longest epic, the dataset comprises over 109K named entity mentions mapped to 5.5K unique entities, and is aligned with an English knowledge base…

The Quasi-Creature and the Uncanny Valley of Agency: A Synthesis of Theory and Evidence on User Interaction with Inconsistent Generative AI
Mauricio Manhaes, Christine Miller, Nicholas Schroeder
https://arxiv.org/abs/2508.18563

The Quasi-Creature and the Uncanny Valley of Agency: A Synthesis of Theory and Evidence on User Interaction with Inconsistent Generative AI
The user experience with large-scale generative AI is paradoxical: superhuman fluency meets absurd failures in common sense and consistency. This paper argues that the resulting potent frustration is an ontological problem, stemming from the "Quasi-Creature"-an entity simulating intelligence without embodiment or genuine understanding. Interaction with this entity precipitates the "Uncanny Valley of Agency," a framework where user comfort drops when highly agentic AI proves erratically unreliab…

Oh you thought the ordeal of being perceived was mortifying? Wait 'till you try being perceived by a state.
As its bureaucratic gaze lingers through the entrails of your medical, financial, scholastic, and social records, a deep disquiet oozes through your brain upon consideration of the labyrinthine antagonisms it may—or may not—inflict upon you. In service only to Capital, this entity has bequeathed immeasurable portions of suffering and death to those it threatens to protect, let alone to its ever-multiplying enemies, and now it is your turn to be found wanting, for in its incessant mechanical hunger, wanting is all that the state can conceive of.
#horror #capitalism #nationalism

On Multi-entity, Multivariate Quickest Change Point Detection
Bahar Kor, Bipin Gaikwad, Abani Patra, Eric L. Miller
https://arxiv.org/abs/2509.18310 https://

On Multi-entity, Multivariate Quickest Change Point Detection
We propose a framework for online Change Point Detection (CPD) from multi-entity, multivariate time series data, motivated by applications in crowd monitoring where traditional sensing methods (e.g., video surveillance) may be infeasible. Our approach addresses the challenge of detecting system-wide behavioral shifts in complex, dynamic environments where the number and behavior of individual entities may be uncertain or evolve. We introduce the concept of Individual Deviation from Normality (I…

Human-Annotated NER Dataset for the Kyrgyz Language
Timur Turatali, Anton Alekseev, Gulira Jumalieva, Gulnara Kabaeva, Sergey Nikolenko
https://arxiv.org/abs/2509.19109 https://…

White House says TikTok's new US entity would lease a copy of ByteDance's algorithm, which Oracle would retrain; US users wouldn't need to re-download the app (Axios)
https://www.axios.com/2025/09/22/tiktok-bytedance-trump-algorithm-lease

Inside Trump's deal to save TikTok
TikTok's new U.S. entity would lease its algorithm from Chinese owner ByteDance.

Trustworthy Semantic Communication for Vehicular Networks: Challenges and Solutions
Yanghe Pan, Yuntao Wang, Shaolong Guo, Chengyu Yin, Ruidong Li, Zhou Su, Yuan Wu
https://arxiv.org/abs/2509.20830

Trustworthy Semantic Communication for Vehicular Networks: Challenges and Solutions
Semantic communication (SemCom) has the potential to significantly reduce communication delay in vehicle-to-everything (V2X) communications within vehicular networks (VNs). However, the deployment of vehicular SemCom networks (VN-SemComNets) faces critical trust challenges in information transmission, semantic encoding, and communication entity reliability. This paper proposes an innovative three-layer trustworthy VN-SemComNet architecture. Specifically, we introduce a semantic camouflage trans…

Transformer-Gather, Fuzzy-Reconsider: A Scalable Hybrid Framework for Entity Resolution
Mohammadreza Sharifi, Danial Ahmadzadeh
https://arxiv.org/abs/2509.17470 https://

Transformer-Gather, Fuzzy-Reconsider: A Scalable Hybrid Framework for Entity Resolution
Entity resolution plays a significant role in enterprise systems where data integrity must be rigorously maintained. Traditional methods often struggle with handling noisy data or semantic understanding, while modern methods suffer from computational costs or the excessive need for parallel computation. In this study, we introduce a scalable hybrid framework, which is designed to address several important problems, including scalability, noise robustness, and reliable results. We utilized a pre…

Nothing plans to invest $100M to spin off budget brand CMF into an independent subsidiary, with India as its manufacturing and R&D headquarters (Ivan Mehta/TechCrunch)
https://techcrunch.com/2025/09/24/smartphone-maker-nothing-to-spin-off-…

Smartphone maker Nothing to spin off its affordable CMF brand | TechCrunch
Nothing is making its affordable devices brand CMF into a separate entity with headquarters in India.

dbpedia_location: DBpedia entity-location network
A bipartite network of the affiliations between named entities from Wikipedia and particular notable locations, as extracted from Wikipedia by the DBpedia project. The date of this snapshot is uncertain.
This network has 225498 nodes and 293697 edges.
Tags: Informational, Relatedness, Unweighted

https://www.stirworld.com/think-opinions-remaking-the-chinese-garden-a-contemporary-architectural-dilemma

Remaking the Chinese Garden: a contemporary architectural dilemma
The Chinese garden is not just a single, independent entity built for crafting landscapes or modelling nature itself, it is a lexicon of symbols, layered upon built reality.

Query-Centric Graph Retrieval Augmented Generation
Yaxiong Wu, Jianyuan Bo, Yongyue Zhang, Sheng Liang, Yong Liu
https://arxiv.org/abs/2509.21237 https://a…

Query-Centric Graph Retrieval Augmented Generation
Graph-based retrieval-augmented generation (RAG) enriches large language models (LLMs) with external knowledge for long-context understanding and multi-hop reasoning, but existing methods face a granularity dilemma: fine-grained entity-level graphs incur high token costs and lose context, while coarse document-level graphs fail to capture nuanced relations. We introduce QCG-RAG, a query-centric graph RAG framework that enables query-granular indexing and multi-hop chunk retrieval. Our query-cen…

Feds allege Bolton mishandled classified info and was hacked by "foreign entity" (Dave Lawler/Axios)
https://www.axios.com/2025/09/12/fbi-bolton-hack-foreign-entity-documents-probe
http://www.memeorandum.com/250912/p136#a250912p136

Oracle, which already provides computing resources for TikTok, would lead “data and privacy” for the new entity.
White House Outlines a TikTok Deal With a U.S. Board
https://www.nytimes.com/2025/09/20/technology/white-house-tiktok-deal.html

White House Outlines a TikTok Deal With a U.S. Board
A potential deal to reduce TikTok’s ties to China would give the app a new board with six American directors out of seven, the White House press secretary said.

"The Metro is alive. It breathes, it listens, it waits. It is not just tunnels and darkness, but a living, breathing entity that holds the souls of those who walk it and reveals truths only to those who are willing to see."
-- Сердар Искандеров
#MetroLastLight #Metro2033

White House says TikTok's new US entity would lease a copy of the algorithm from ByteDance, which Oracle would retrain; users won't need to re-download the app (Axios)
https://www.axios.com/2025/09/22/tiktok-bytedance-trump-algorithm-lease

Inside Trump's deal to save TikTok
TikTok's new U.S. entity would lease its algorithm from Chinese owner ByteDance.

QDER: Query-Specific Document and Entity Representations for Multi-Vector Document Re-Ranking
Shubham Chatterjee, Jeff Dalton
https://arxiv.org/abs/2510.11589 https://

QDER: Query-Specific Document and Entity Representations for Multi-Vector Document Re-Ranking
Neural IR has advanced through two distinct paths: entity-oriented approaches leveraging knowledge graphs and multi-vector models capturing fine-grained semantics. We introduce QDER, a neural re-ranking model that unifies these approaches by integrating knowledge graph semantics into a multi-vector model. QDER's key innovation lies in its modeling of query-document relationships: rather than computing similarity scores on aggregated embeddings, we maintain individual token and entity representa…

Retrieval over Classification: Integrating Relation Semantics for Multimodal Relation Extraction
Lei Hei, Tingjing Liao, Yingxin Pei, Yiyang Qi, Jiaqi Wang, Ruiting Li, Feiliang Ren
https://arxiv.org/abs/2509.21151

Retrieval over Classification: Integrating Relation Semantics for Multimodal Relation Extraction
Relation extraction (RE) aims to identify semantic relations between entities in unstructured text. Although recent work extends traditional RE to multimodal scenarios, most approaches still adopt classification-based paradigms with fused multimodal features, representing relations as discrete labels. This paradigm has two significant limitations: (1) it overlooks structural constraints like entity types and positional cues, and (2) it lacks semantic expressiveness for fine-grained relation und…

It was a challenging week for Americans that strongly assert that organisations enforcing their own standards to supress speech cannot be censorship, even if that action is as a result of backroom coercion from a more powerful entity that may or may not be a government.

I could have written "maybe we rely a bit too much on these giant server farms owned by a single entity?" but I like the more silly and less serious approach to the discussion.
Beside, writing it here I'm just preaching the quire. So we might have some fun meanwhile!

EcphoryRAG: Re-Imagining Knowledge-Graph RAG via Human Associative Memory
Zirui Liao
https://arxiv.org/abs/2510.08958 https://arxiv.org/pdf/2510.08958

EcphoryRAG: Re-Imagining Knowledge-Graph RAG via Human Associative Memory
Cognitive neuroscience research indicates that humans leverage cues to activate entity-centered memory traces (engrams) for complex, multi-hop recollection. Inspired by this mechanism, we introduce EcphoryRAG, an entity-centric knowledge graph RAG framework. During indexing, EcphoryRAG extracts and stores only core entities with corresponding metadata, a lightweight approach that reduces token consumption by up to 94\% compared to other structured RAG systems. For retrieval, the system first ex…

D-party congress critters ought to begin drafting bills to dismantle DHS.
DHS, including its highly nazi-flavored name, was constructed by a Congress and president (bush) who were terrified after 9/11.
It is time to pull the pieces of DHS apart, retaining some parts, deleting other parts (such as ICE), and reshaping the rest.
There is a rule of thumb that suggests that if one wants to re-form an entity to change its internal culture that no more than 10% of the staff should…

Got this email and thought, "Ha that is a scam. There is no way that the real Paypal would provide a link to update to login and card details!" 🤣
I mean they are a well known entity, with a well known domain, they can just tell you to do it. It's not like you don't know the URL.
But no, that is exactly what they have done. 🤯
P.S. Paypal, yes I know but sometimes it is the only way to pay. 😢

Ground-Based Radar Tracking of Near-Earth Objects With VLBI Radio Telescopes: 2024 MK Test Case
Oliver White, Guifr\'e Molera Calv\'es, Shinji Horiuchi, Ed Kruzins, Edwin Peters, Nick Stacy
https://arxiv.org/abs/2509.15684

Ground-Based Radar Tracking of Near-Earth Objects With VLBI Radio Telescopes: 2024 MK Test Case
The Southern Hemisphere Asteroid Research Project is an active and informal entity comprising the University of New South Wales, the University of Tasmania, the University of Western Australia, and the Curtin University, which performs asteroid research in collaboration with federal agencies, including the Commonwealth Scientific and Industrial Research Organisation and the National Aeronautics and Space Administration (JPL). Since 2015, we have used the Australian infrastructure to characteriz…

"The Securing American Funding and Expertise from Adversarial Research Exploitation (SAFE) Act would deny federal funding to any U.S. scientist who collaborates with anyone “affiliated with a hostile foreign entity,” a category that includes four countries: China, Russia, Iran, and North Korea. The prohibited activities would include joint research, co-authorship on papers, and advising a foreign graduate student or postdoctoral fellow. The language is retroactive, meaning any interactions during the previous 5 years could make a scientist ineligible for future federal funding."
https://www.science.org/content/article/u-s-congress-considers-sweeping-ban-chinese-collaborations

@…
I can't tell if you're the same entity as the people adding so-called AI to Firefox, are you? Or can you pass a message on?
My message would be: Firefox would be much more valuable as a privacy-first, climate-conscious, efficient alternative to the other browsers jumping on the LLM bandwagon.
#Firefox #Mozilla

GenCNER: A Generative Framework for Continual Named Entity Recognition
Yawen Yang, Fukun Ma, Shiao Meng, Aiwei Liu, Lijie Wen
https://arxiv.org/abs/2510.11444 https://

GenCNER: A Generative Framework for Continual Named Entity Recognition
Traditional named entity recognition (NER) aims to identify text mentions into pre-defined entity types. Continual Named Entity Recognition (CNER) is introduced since entity categories are continuously increasing in various real-world scenarios. However, existing continual learning (CL) methods for NER face challenges of catastrophic forgetting and semantic shift of non-entity type. In this paper, we propose GenCNER, a simple but effective Generative framework for CNER to mitigate the above dra…

My guess here at a distance is that it’s a terrible mistake to think of “Harvard” as a single anthropomorphic entity with a single mind. There are surely terrible internal battles raging at Harvard right now: between those who think it’s truly for education and those who think it’s truly for ROI, between those protecting the dollars and those protecting the brand reputation, between those cowering at the short-term financial risk of angering an authoritarian and those who see the long-term risks of capitulating.
What does “Harvard” think? Harvard is a bunch of different people. I wish them luck, and wisdom. Heaven knows they’ll need it.
/end

dbpedia_location: DBpedia entity-location network
A bipartite network of the affiliations between named entities from Wikipedia and particular notable locations, as extracted from Wikipedia by the DBpedia project. The date of this snapshot is uncertain.
This network has 225498 nodes and 293697 edges.
Tags: Informational, Relatedness, Unweighted

“What we seem to have here is yet another instance of a massive corporate entity capitulating to the emperor’s wishes in advance, but this one is particularly frustrating because there is less for the average consumer like you and me to do about it.” https://apple.news/AIOs-uVO9S62q7E2-cg0v2A

In Canada, the CBC might be the kind of entity to help run / coordinate “public service social media” as described in this Tech Policy Press article https://www.techpolicy.press/public-service-social-media-as-a-democratic-safeguard/
With interop…

NER Retriever: Zero-Shot Named Entity Retrieval with Type-Aware Embeddings
Or Shachar, Uri Katz, Yoav Goldberg, Oren Glickman
https://arxiv.org/abs/2509.04011 https://

NER Retriever: Zero-Shot Named Entity Retrieval with Type-Aware Embeddings
We present NER Retriever, a zero-shot retrieval framework for ad-hoc Named Entity Retrieval, a variant of Named Entity Recognition (NER), where the types of interest are not provided in advance, and a user-defined type description is used to retrieve documents mentioning entities of that type. Instead of relying on fixed schemas or fine-tuned models, our method builds on internal representations of large language models (LLMs) to embed both entity mentions and user-provided open-ended type desc…

NERVIS: An Interactive System for Graph-Based Exploration and Editing of Named Entities
Uro\v{s} \v{S}majdek, Ciril Bohak
https://arxiv.org/abs/2510.04971 https://

NERVIS: An Interactive System for Graph-Based Exploration and Editing of Named Entities
We present an interactive visualization system for exploring named entities and their relationships across document collections. The system is designed around a graph-based representation that integrates three types of nodes: documents, entity mentions, and entities. Connections capture two key relationship types: (i) identical entities across contexts, and (ii) co-locations of mentions within documents. Multiple coordinated views enable users to examine entity occurrences, discover clusters of…

NASA will get a safety process cut before it gets money to satisfy the empty promise from this administration. Folks will die, Trump will blame scientists, install yet more political hacks, and leave office having achieved nothing more than hollowing out another science-based government entity.

NASA’s acting chief “angry” about talk that China will beat US back to the Moon
“I can tell you what, I’ll be damned if that is the story that we write.”…

Wednesday’s discovery exposes a key weakness of the public key infrastructure that’s responsible for ensuring trust of the entire Internet.
Despite being the only thing ensuring that gmail.com, bankofamerica.com or any other website is controlled by the entity claiming ownership,
the entire system can collapse with a single point of failure.
The Certificate Authority ecosystem is a castle with many doors:
the failure of one CA can cause the security of the whole cast…

Mis-issued certificates for 1.1.1.1 DNS service pose a threat to the Internet
The three certificates were issued in May but only came to light Wednesday.

VeilAudit: Breaking the Deadlock Between Privacy and Accountability Across Blockchains
Minhao Qiao, Iqbal Gondal, Hai Dong
https://arxiv.org/abs/2510.12153 https://

VeilAudit: Breaking the Deadlock Between Privacy and Accountability Across Blockchains
Cross chain interoperability in blockchain systems exposes a fundamental tension between user privacy and regulatory accountability. Existing solutions enforce an all or nothing choice between full anonymity and mandatory identity disclosure, which limits adoption in regulated financial settings. We present VeilAudit, a cross chain auditing framework that introduces Auditor Only Linkability, which allows auditors to link transaction behaviors that originate from the same anonymous entity withou…

"Archaeologists: D.C. Capitol May Once Have Been Used For Legislating"

Dynamic Span Interaction and Graph-Aware Memory for Entity-Level Sentiment Classification
Md. Mithun Hossain, Sanjara, Md. Shakil Hossain, Sudipto Chaki
https://arxiv.org/abs/2509.11604

Dynamic Span Interaction and Graph-Aware Memory for Entity-Level Sentiment Classification
Entity-level sentiment classification involves identifying the sentiment polarity linked to specific entities within text. This task poses several challenges: effectively modeling the subtle and complex interactions between entities and their surrounding sentiment expressions; capturing dependencies that may span across sentences; and ensuring consistent sentiment predictions for multiple mentions of the same entity through coreference resolution. Additionally, linguistic phenomena such as nega…

British renewable energy startup Octopus Energy spins off its AI arm, Kraken, in what could create a stand-alone entity worth $15B (Yusuf Khan/Wall Street Journal)
https://www.wsj.com/articles/octopus-energy-to-s…

Replaced article(s) found for cs.PL. https://arxiv.org/list/cs.PL/new
[1/1]:
- Exploring the Theory and Practice of Concurrency in the Entity-Component-System Pattern
Patrick Redmond, Jonathan Castello, Jos\'e Manuel Calder\'on Trilla, Lindsey Kuper

HECATE: An ECS-based Framework for Teaching and Developing Multi-Agent Systems
Arthur Casals, Anarosa A. F. Brand\~ao
https://arxiv.org/abs/2509.06431 https://

HECATE: An ECS-based Framework for Teaching and Developing Multi-Agent Systems
This paper introduces HECATE, a novel framework based on the Entity-Component-System (ECS) architectural pattern that bridges the gap between distributed systems engineering and MAS development. HECATE is built using the Entity-Component-System architectural pattern, leveraging data-oriented design to implement multiagent systems. This approach involves engineering multiagent systems (MAS) from a distributed systems (DS) perspective, integrating agent concepts directly into the DS domain. This …

@… TIL:
<https://en.wikipedia.org/wiki/Jumping_the_shark>
＂… a creative work or entity has evolved and reached a point in which it has exh…

dbpedia_location: DBpedia entity-location network
A bipartite network of the affiliations between named entities from Wikipedia and particular notable locations, as extracted from Wikipedia by the DBpedia project. The date of this snapshot is uncertain.
This network has 225498 nodes and 293697 edges.
Tags: Informational, Relatedness, Unweighted

Superellipsoid modeling of wire-laser additive manufacturing defects measured by digital image correlation
Khalil Hachem (LURPA), Yann Quinsat (LURPA), Christophe Tournier (LURPA), Nicolas Beraud (G-SCOP)
https://arxiv.org/abs/2509.17545

Superellipsoid modeling of wire-laser additive manufacturing defects measured by digital image correlation
In wire-laser additive manufacturing (WLAM), producing parts with multiple entities requires optimizing both additive and subtractive processes. This involves adjusting positions and integrating machining operations. Geometric defects that occur during the components' deposition can affect subsequent entity production, making real-time measurement crucial. A contactless measuring system is essential to assess geometric deviations without complex post-processing. A comprehensive image stereocorr…

BIBERT-Pipe on Biomedical Nested Named Entity Linking at BioASQ 2025
Chunyu Li, Xindi Zheng, Siqi Liu
https://arxiv.org/abs/2509.09725 https://arxiv.org/pd…

BIBERT-Pipe on Biomedical Nested Named Entity Linking at BioASQ 2025
Entity linking (EL) for biomedical text is typically benchmarked on English-only corpora with flat mentions, leaving the more realistic scenario of nested and multilingual mentions largely unexplored. We present our system for the BioNNE 2025 Multilingual Biomedical Nested Named Entity Linking shared task (English & Russian), closing this gap with a lightweight pipeline that keeps the original EL model intact and modifies only three task-aligned components: Two-stage retrieval-ranking. We lever…

I made the mistake of reading the comments here on a story about Charlie Kirk yesterday. I like Mastodon because it's not owned by a single entity. I made the mistake of assuming my other values would therefore be shared by those here. But there was a disturbing number who apparently condone murder. I cannot do that.

Replaced article(s) found for cs.SE. https://arxiv.org/list/cs.SE/new
[1/1]:
- ETF: An Entity Tracing Framework for Hallucination Detection in Code Summaries
Maharaj, Munigala, Tamilselvam, Kumar, Sen, Kodeswaran, Mishra, Bhattacharyya

Understanding Fanchuan in Livestreaming Platforms: A New Form of Online Antisocial Behavior
Yiluo Wei, Jiahui He, Gareth Tyson
https://arxiv.org/abs/2509.00780 https://

Understanding Fanchuan in Livestreaming Platforms: A New Form of Online Antisocial Behavior
Recently, a distinct form of online antisocial behavior, known as "fanchuan", has emerged across online platforms, particularly in livestreaming chats. Fanchuan is an indirect attack on a specific entity, such as a celebrity, video game, or brand. It entails two main actions: (i) individuals first feign support for the entity, and exhibit this allegiance widely; (ii) they then engage in offensive or irritating behavior, attempting to undermine the entity by association. This deceptive conduct i…

Optimal Control Meets Flow Matching: A Principled Route to Multi-Subject Fidelity
Eric Tillmann Bill, Enis Simsar, Thomas Hofmann
https://arxiv.org/abs/2510.02315 https://

Optimal Control Meets Flow Matching: A Principled Route to Multi-Subject Fidelity
Text-to-image (T2I) models excel on single-entity prompts but struggle with multi-subject descriptions, often showing attribute leakage, identity entanglement, and subject omissions. We introduce the first theoretical framework with a principled, optimizable objective for steering sampling dynamics toward multi-subject fidelity. Viewing flow matching (FM) through stochastic optimal control (SOC), we formulate subject disentanglement as control over a trained FM sampler. This yields two architec…

REGENT: Relevance-Guided Attention for Entity-Aware Multi-Vector Neural Re-Ranking
Shubham Chatterjee
https://arxiv.org/abs/2510.11592 https://arxiv.org/pd…

REGENT: Relevance-Guided Attention for Entity-Aware Multi-Vector Neural Re-Ranking
Current neural re-rankers often struggle with complex information needs and long, content-rich documents. The fundamental issue is not computational--it is intelligent content selection: identifying what matters in lengthy, multi-faceted texts. While humans naturally anchor their understanding around key entities and concepts, neural models process text within rigid token windows, treating all interactions as equally important and missing critical semantic signals. We introduce REGENT, a neural…

FusionAdapter for Few-Shot Relation Learning in Multimodal Knowledge Graphs
Ran Liu, Yuan Fang, Xiaoli Li
https://arxiv.org/abs/2510.00894 https://arxiv.or…

FusionAdapter for Few-Shot Relation Learning in Multimodal Knowledge Graphs
Multimodal Knowledge Graphs (MMKGs) incorporate various modalities, including text and images, to enhance entity and relation representations. Notably, different modalities for the same entity often present complementary and diverse information. However, existing MMKG methods primarily align modalities into a shared space, which tends to overlook the distinct contributions of specific modalities, limiting their performance particularly in low-resource settings. To address this challenge, we pro…

The NYDFS grants Bullish a BitLicense, allowing its US entity to offer spot trading and custody services in the state (CoinDesk)
https://www.coindesk.com/policy/2025/09/17/crypto-platform-bullish-wins-new-york-bitlic…

US investors in spyware firms nearly tripled in 2024: report https://therecord.media/us-investors-in-spyware-tripled-in-2024

ALLabel: Three-stage Active Learning for LLM-based Entity Recognition using Demonstration Retrieval
Zihan Chen, Lei Shi, Weize Wu, Qiji Zhou, Yue Zhang
https://arxiv.org/abs/2509.07512

ALLabel: Three-stage Active Learning for LLM-based Entity Recognition using Demonstration Retrieval
Many contemporary data-driven research efforts in the natural sciences, such as chemistry and materials science, require large-scale, high-performance entity recognition from scientific datasets. Large language models (LLMs) have increasingly been adopted to solve the entity recognition task, with the same trend being observed on all-spectrum NLP tasks. The prevailing entity recognition LLMs rely on fine-tuned technology, yet the fine-tuning process often incurs significant cost. To achieve a b…

Enhancing Credit Risk Prediction: A Meta-Learning Framework Integrating Baseline Models, LASSO, and ECOC for Superior Accuracy
Haibo Wang, Lutfu S. Sua, Jun Huang, Figen Balo, Burak Dolar
https://arxiv.org/abs/2509.22381

Enhancing Credit Risk Prediction: A Meta-Learning Framework Integrating Baseline Models, LASSO, and ECOC for Superior Accuracy
Effective credit risk management is fundamental to financial decision-making, necessitating robust models for default probability prediction and financial entity classification. Traditional machine learning approaches face significant challenges when confronted with high-dimensional data, limited interpretability, rare event detection, and multi-class imbalance problems in risk assessment. This research proposes a comprehensive meta-learning framework that synthesizes multiple complementary mod…

dbpedia_location: DBpedia entity-location network
A bipartite network of the affiliations between named entities from Wikipedia and particular notable locations, as extracted from Wikipedia by the DBpedia project. The date of this snapshot is uncertain.
This network has 225498 nodes and 293697 edges.
Tags: Informational, Relatedness, Unweighted

Bi-Level Game-Theoretic Planning of Cyber Deception for Cognitive Arbitrage
Ya-Ting Yang, Quanyan Zhu
https://arxiv.org/abs/2509.05498 https://arxiv.org/pd…

Bi-Level Game-Theoretic Planning of Cyber Deception for Cognitive Arbitrage
Cognitive vulnerabilities shape human decision-making and arise primarily from two sources: (1) cognitive capabilities, which include disparities in knowledge, education, expertise, or access to information, and (2) cognitive biases, such as rational inattention, confirmation bias, and base rate neglect, which influence how individuals perceive and process information. Exploiting these vulnerabilities allows an entity with superior cognitive awareness to gain a strategic advantage, a concept re…

In what Public Citizen called
"the greatest corruption in presidential history,"
Donald Trumpand his family added $5 billion in cash to their fortunes this Labor Day
as his new cryptocurrency was opened to the public market.
The currency, known as WLFI,
is owned by World Liberty Financial,
a company founded by the president's sons, Donald Trump, Jr., and Eric Trump.
A Trump business entity owns 60% of the company and is entitled to 75% …

'Greatest Corruption in Presidential History': Trump Family Reaps $5 Billion More in Crypto Profits | Common Dreams
In what Public Citizen called "the greatest corruption in presidential history," US President Donald Trump and his family added $5 billion in cash to their fortunes this Labor Day as his new cryptocurrency was opened to the public market.

Replaced article(s) found for cs.AI. https://arxiv.org/list/cs.AI/new
[3/6]:
- Query Brand Entity Linking in E-Commerce Search
Dong Liu, Sreyashi Nag
https://

Decoupled Entity Representation Learning for Pinterest Ads Ranking
Jie Liu, Yinrui Li, Jiankai Sun, Kungang Li, Han Sun, Sihan Wang, Huasen Wu, Siyuan Gao, Paulo Soares, Nan Li, Zhifang Liu, Haoyang Li, Siping Ji, Ling Leng, Prathibha Deshikachar
https://arxiv.org/abs/2509.04337

Decoupled Entity Representation Learning for Pinterest Ads Ranking
In this paper, we introduce a novel framework following an upstream-downstream paradigm to construct user and item (Pin) embeddings from diverse data sources, which are essential for Pinterest to deliver personalized Pins and ads effectively. Our upstream models are trained on extensive data sources featuring varied signals, utilizing complex architectures to capture intricate relationships between users and Pins on Pinterest. To ensure scalability of the upstream models, entity embeddings are …

dbpedia_location: DBpedia entity-location network
A bipartite network of the affiliations between named entities from Wikipedia and particular notable locations, as extracted from Wikipedia by the DBpedia project. The date of this snapshot is uncertain.
This network has 225498 nodes and 293697 edges.
Tags: Informational, Relatedness, Unweighted

Towards Adaptive Context Management for Intelligent Conversational Question Answering
Manoj Madushanka Perera, Adnan Mahmood, Kasun Eranda Wijethilake, Quan Z. Sheng
https://arxiv.org/abs/2509.17829

Towards Adaptive Context Management for Intelligent Conversational Question Answering
This particular paper introduces an Adaptive Context Management (ACM) framework for the Conversational Question Answering (ConvQA) systems. The key objective of the ACM framework is to optimize the use of the conversation history by dynamically managing context for maximizing the relevant information provided to a ConvQA model within its token limit. Our approach incorporates a Context Manager (CM) Module, a Summarization (SM) Module, and an Entity Extraction (EE) Module in a bid to handle the …

Replaced article(s) found for cs.CV. https://arxiv.org/list/cs.CV/new
[8/9]:
- Advancing Grounded Multimodal Named Entity Recognition via LLM-Based Reformulation and Box-Based ...
Jinyuan Li, Ziyan Li, Han Li, Jianfei Yu, Rui Xia, Di Sun, Gang Pan

SciEvent: Benchmarking Multi-domain Scientific Event Extraction
Bofu Dong, Pritesh Shah, Sumedh Sonawane, Tiyasha Banerjee, Erin Brady, Xinya Du, Ming Jiang
https://arxiv.org/abs/2509.15620

SciEvent: Benchmarking Multi-domain Scientific Event Extraction
Scientific information extraction (SciIE) has primarily relied on entity-relation extraction in narrow domains, limiting its applicability to interdisciplinary research and struggling to capture the necessary context of scientific information, often resulting in fragmented or conflicting statements. In this paper, we introduce SciEvent, a novel multi-domain benchmark of scientific abstracts annotated via a unified event extraction (EE) schema designed to enable structured and context-aware unde…

FusionAdapter for Few-Shot Relation Learning in Multimodal Knowledge Graphs
Ran Liu, Yuan Fang, Xiaoli Li
https://arxiv.org/abs/2510.00894 https://arxiv.or…

FusionAdapter for Few-Shot Relation Learning in Multimodal Knowledge Graphs
Multimodal Knowledge Graphs (MMKGs) incorporate various modalities, including text and images, to enhance entity and relation representations. Notably, different modalities for the same entity often present complementary and diverse information. However, existing MMKG methods primarily align modalities into a shared space, which tends to overlook the distinct contributions of specific modalities, limiting their performance particularly in low-resource settings. To address this challenge, we pro…

Replaced article(s) found for cs.DB. https://arxiv.org/list/cs.DB/new
[1/1]:
- FastER: On-Demand Entity Resolution in Property Graphs
Wang, Zhao, Miao, Kwashie, Bewong, Hu, Nofong, Feng
…

dbpedia_location: DBpedia entity-location network
A bipartite network of the affiliations between named entities from Wikipedia and particular notable locations, as extracted from Wikipedia by the DBpedia project. The date of this snapshot is uncertain.
This network has 225498 nodes and 293697 edges.
Tags: Informational, Relatedness, Unweighted

The strikes on the Venezuelan boats
-- allegedly carrying "narcotics"
-- which the administration has claimed were necessary because interdiction "did not work,"
have been orchestrated through the homeland security council (HSC)
-- which Stephen Miller leads
as the homeland security adviser.
Miller empowered the HSC earlier this year to become its own entity in Donald Trump’s second term
-- a notable departure from previous administ…

PGMEL: Policy Gradient-based Generative Adversarial Network for Multimodal Entity Linking
KM Pooja, Cheng Long, Aixin Sun
https://arxiv.org/abs/2510.02726 https://

PGMEL: Policy Gradient-based Generative Adversarial Network for Multimodal Entity Linking
The task of entity linking, which involves associating mentions with their respective entities in a knowledge graph, has received significant attention due to its numerous potential applications. Recently, various multimodal entity linking (MEL) techniques have been proposed, targeted to learn comprehensive embeddings by leveraging both text and vision modalities. The selection of high-quality negative samples can potentially play a crucial role in metric/representation learning. However, to th…

SecureBERT 2.0: Advanced Language Model for Cybersecurity Intelligence
Ehsan Aghaei, Sarthak Jain, Prashanth Arun, Arjun Sambamoorthy
https://arxiv.org/abs/2510.00240 https://…

SecureBERT 2.0: Advanced Language Model for Cybersecurity Intelligence
Effective analysis of cybersecurity and threat intelligence data demands language models that can interpret specialized terminology, complex document structures, and the interdependence of natural language and source code. Encoder-only transformer architectures provide efficient and robust representations that support critical tasks such as semantic search, technical entity extraction, and semantic analysis, which are key to automated threat detection, incident triage, and vulnerability assessm…

RANGER -- Repository-Level Agent for Graph-Enhanced Retrieval
Pratik Shah, Rajat Ghosh, Aryan Singhal, Debojyoti Dutta
https://arxiv.org/abs/2509.25257 https://

RANGER -- Repository-Level Agent for Graph-Enhanced Retrieval
General-purpose automated software engineering (ASE) includes tasks such as code completion, retrieval, repair, QA, and summarization. These tasks require a code retrieval system that can handle specific queries about code entities, or code entity queries (for example, locating a specific class or retrieving the dependencies of a function), as well as general queries without explicit code entities, or natural language queries (for example, describing a task and retrieving the corresponding code…

PARCO: Phoneme-Augmented Robust Contextual ASR via Contrastive Entity Disambiguation
Jiajun He, Naoki Sawada, Koichi Miyazaki, Tomoki Toda
https://arxiv.org/abs/2509.04357 https…

PARCO: Phoneme-Augmented Robust Contextual ASR via Contrastive Entity Disambiguation
Automatic speech recognition (ASR) systems struggle with domain-specific named entities, especially homophones. Contextual ASR improves recognition but often fails to capture fine-grained phoneme variations due to limited entity diversity. Moreover, prior methods treat entities as independent tokens, leading to incomplete multi-token biasing. To address these issues, we propose Phoneme-Augmented Robust Contextual ASR via COntrastive entity disambiguation (PARCO), which integrates phoneme-aware …

ReFineG: Synergizing Small Supervised Models and LLMs for Low-Resource Grounded Multimodal NER
Jielong Tang, Shuang Wang, Zhenxing Wang, Jianxing Yu, Jian Yin
https://arxiv.org/abs/2509.10975

ReFineG: Synergizing Small Supervised Models and LLMs for Low-Resource Grounded Multimodal NER
Grounded Multimodal Named Entity Recognition (GMNER) extends traditional NER by jointly detecting textual mentions and grounding them to visual regions. While existing supervised methods achieve strong performance, they rely on costly multimodal annotations and often underperform in low-resource domains. Multimodal Large Language Models (MLLMs) show strong generalization but suffer from Domain Knowledge Conflict, producing redundant or incorrect mentions for domain-specific entities. To address…

SciNLP: A Domain-Specific Benchmark for Full-Text Scientific Entity and Relation Extraction in NLP
Decheng Duan, Yingyi Zhang, Jitong Peng, Chengzhi Zhang
https://arxiv.org/abs/2509.07801

SciNLP: A Domain-Specific Benchmark for Full-Text Scientific Entity and Relation Extraction in NLP
Structured information extraction from scientific literature is crucial for capturing core concepts and emerging trends in specialized fields. While existing datasets aid model development, most focus on specific publication sections due to domain complexity and the high cost of annotating scientific texts. To address this limitation, we introduce SciNLP - a specialized benchmark for full-text entity and relation extraction in the Natural Language Processing (NLP) domain. The dataset comprises …

The US Commerce Department says subsidiaries of entity list companies would also be subject to trade restrictions, threatening Chinese companies, from Tuesday (Amrith Ramkumar/Wall Street Journal)
https://www.

Is 'Hope' a person or an idea? A pilot benchmark for NER: comparing traditional NLP tools and large language models on ambiguous entities
Payam Latifi
https://arxiv.org/abs/2509.12098

Is 'Hope' a person or an idea? A pilot benchmark for NER: comparing traditional NLP tools and large language models on ambiguous entities
This pilot study presents a small-scale but carefully annotated benchmark of Named Entity Recognition (NER) performance across six systems: three non-LLM NLP tools (NLTK, spaCy, Stanza) and three general-purpose large language models (LLMs: Gemini-1.5-flash, DeepSeek-V3, Qwen-3-4B). The dataset contains 119 tokens covering five entity types (PERSON, LOCATION, ORGANIZATION, DATE, TIME). We evaluated each system's output against the manually annotated gold standard dataset using F1-score. The res…

HCCM: Hierarchical Cross-Granularity Contrastive and Matching Learning for Natural Language-Guided Drones
Hao Ruan, Jinliang Lin, Yingxin Lai, Zhiming Luo, Shaozi Li
https://arxiv.org/abs/2508.21539

HCCM: Hierarchical Cross-Granularity Contrastive and Matching Learning for Natural Language-Guided Drones
Natural Language-Guided Drones (NLGD) provide a novel paradigm for tasks such as target matching and navigation. However, the wide field of view and complex compositional semantics in drone scenarios pose challenges for vision-language understanding. Mainstream Vision-Language Models (VLMs) emphasize global alignment while lacking fine-grained semantics, and existing hierarchical methods depend on precise entity partitioning and strict containment, limiting effectiveness in dynamic environments…

WUGNECTIVES: Novel Entity Inferences of Language Models from Discourse Connectives
Daniel Brubaker, William Sheffield, Junyi Jessy Li, Kanishka Misra
https://arxiv.org/abs/2510.09556

WUGNECTIVES: Novel Entity Inferences of Language Models from Discourse Connectives
The role of world knowledge has been particularly crucial to predict the discourse connective that marks the discourse relation between two arguments, with language models (LMs) being generally successful at this task. We flip this premise in our work, and instead study the inverse problem of understanding whether discourse connectives can inform LMs about the world. To this end, we present WUGNECTIVES, a dataset of 8,880 stimuli that evaluates LMs' inferences about novel entities in contexts w…

Pharmaceutical company Eversana acquires Waltz Health, which provides drug price-comparison software to insurance companies, creating an entity valued at $6B (John Tozzi/Bloomberg)
https://www.bloomberg.com/news/articles/20

Powering Job Search at Scale: LLM-Enhanced Query Understanding in Job Matching Systems
Ping Liu, Jianqiang Shen, Qianqi Shen, Chunnan Yao, Kevin Kao, Dan Xu, Rajat Arora, Baofen Zheng, Caleb Johnson, Liangjie Hong, Jingwei Wu, Wenjing Zhang
https://arxiv.org/abs/2509.09690

Powering Job Search at Scale: LLM-Enhanced Query Understanding in Job Matching Systems
Query understanding is essential in modern relevance systems, where user queries are often short, ambiguous, and highly context-dependent. Traditional approaches often rely on multiple task-specific Named Entity Recognition models to extract structured facets as seen in job search applications. However, this fragmented architecture is brittle, expensive to maintain, and slow to adapt to evolving taxonomies and language patterns. In this paper, we introduce a unified query understanding framewor…

Sources: Saudi Arabia's PIF is the largest contributor to the $36B in equity used to finance the EA deal; it will roll over its $5B EA stake into the new entity (Bloomberg)
https://www.bloomberg.com/news/articles/2025-09-29/s…

NE-PADD: Leveraging Named Entity Knowledge for Robust Partial Audio Deepfake Detection via Attention Aggregation
Huhong Xian, Rui Liu, Berrak Sisman, Haizhou Li
https://arxiv.org/abs/2509.03829

NE-PADD: Leveraging Named Entity Knowledge for Robust Partial Audio Deepfake Detection via Attention Aggregation
Different from traditional sentence-level audio deepfake detection (ADD), partial audio deepfake detection (PADD) requires frame-level positioning of the location of fake speech. While some progress has been made in this area, leveraging semantic information from audio, especially named entities, remains an underexplored aspect. To this end, we propose NE-PADD, a novel method for Partial Audio Deepfake Detection (PADD) that leverages named entity knowledge through two parallel branches: Speech …

Generative Annotation for ASR Named Entity Correction
Yuanchang Luo, Daimeng Wei, Shaojun Li, Hengchao Shang, Jiaxin Guo, Zongyao Li, Zhanglin Wu, Xiaoyu Chen, Zhiqiang Rao, Jinlong Yang, Hao Yang
https://arxiv.org/abs/2508.20700

Generative Annotation for ASR Named Entity Correction
End-to-end automatic speech recognition systems often fail to transcribe domain-specific named entities, causing catastrophic failures in downstream tasks. Numerous fast and lightweight named entity correction (NEC) models have been proposed in recent years. These models, mainly leveraging phonetic-level edit distance algorithms, have shown impressive performances. However, when the forms of the wrongly-transcribed words(s) and the ground-truth entity are significantly different, these methods …

Sources: data integration company Fivetran is in talks to acquire data management company dbt Labs in a deal valuing the combined entity at between $5B and $10B (The Information)
https://www.theinformation.com/articles/data-startup-fi…

Data Startup Fivetran In Talks to Buy Dbt Labs in Multibillion Dollar Deal
Fivetran, a startup used by companies to manage and prepare data for analytics and artificial intelligence, is in talks to buy data management companydbt Labs, according to people with direct knowledge of the deal. The deal would combine two data companies that are facing competition from ...

Meta-Pretraining for Zero-Shot Cross-Lingual Named Entity Recognition in Low-Resource Philippine Languages
David Demitri Africa, Suchir Salhan, Yuval Weiss, Paula Buttery, Richard Diehl Martinez
https://arxiv.org/abs/2509.02160

Meta-Pretraining for Zero-Shot Cross-Lingual Named Entity Recognition in Low-Resource Philippine Languages
Named-entity recognition (NER) in low-resource languages is usually tackled by finetuning very large multilingual LMs, an option that is often infeasible in memory- or latency-constrained settings. We ask whether small decoder LMs can be pretrained so that they adapt quickly and transfer zero-shot to languages unseen during pretraining. To this end we replace part of the autoregressive objective with first-order model-agnostic meta-learning (MAML). Tagalog and Cebuano are typologically similar …

Comparative Study of Pre-Trained BERT and Large Language Models for Code-Mixed Named Entity Recognition
Mayur Shirke, Amey Shembade, Pavan Thorat, Madhushri Wagh, Raviraj Joshi
https://arxiv.org/abs/2509.02514

Comparative Study of Pre-Trained BERT and Large Language Models for Code-Mixed Named Entity Recognition
Named Entity Recognition (NER) in code-mixed text, particularly Hindi-English (Hinglish), presents unique challenges due to informal structure, transliteration, and frequent language switching. This study conducts a comparative evaluation of code-mixed fine-tuned models and non-code-mixed multilingual models, along with zero-shot generative large language models (LLMs). Specifically, we evaluate HingBERT, HingMBERT, and HingRoBERTa (trained on code-mixed data), and BERT Base Cased, IndicBERT, R…

On the Representations of Entities in Auto-regressive Large Language Models
Victor Morand, Josiane Mothe, Benjamin Piwowarski
https://arxiv.org/abs/2510.09421 https://

On the Representations of Entities in Auto-regressive Large Language Models
Named entities are fundamental building blocks of knowledge in text, grounding factual information and structuring relationships within language. Despite their importance, it remains unclear how Large Language Models (LLMs) internally represent entities. Prior research has primarily examined explicit relationships, but little is known about entity representations themselves. We introduce entity mention reconstruction as a novel framework for studying how LLMs encode and manipulate entities. We …

Crosslisted article(s) found for cs.IR. https://arxiv.org/list/cs.IR/new
[1/1]:
- ALLabel: Three-stage Active Learning for LLM-based Entity Recognition using Demonstration Retrieval
Zihan Chen, Lei Shi, Weize Wu, Qiji Zhou, Yue Zhang

Using LLMs for Multilingual Clinical Entity Linking to ICD-10
Sylvia Vassileva, Ivan Koychev, Svetla Boytcheva
https://arxiv.org/abs/2509.04868 https://arx…

Using LLMs for Multilingual Clinical Entity Linking to ICD-10
The linking of clinical entities is a crucial part of extracting structured information from clinical texts. It is the process of assigning a code from a medical ontology or classification to a phrase in the text. The International Classification of Diseases - 10th revision (ICD-10) is an international standard for classifying diseases for statistical and insurance purposes. Automatically assigning the correct ICD-10 code to terms in discharge summaries will simplify the work of healthcare prof…

HistoryBankQA: Multilingual Temporal Question Answering on Historical Events
Biswadip Mandal, Anant Khandelwal, Manish Gupta
https://arxiv.org/abs/2509.12720 https://

HistoryBankQA: Multilingual Temporal Question Answering on Historical Events
Temporal reasoning about historical events is a critical skill for NLP tasks like event extraction, historical entity linking, temporal question answering, timeline summarization, temporal event clustering and temporal natural language inference. Yet efforts on benchmarking temporal reasoning capabilities of large language models (LLMs) are rather limited. Existing temporal reasoning datasets are limited in scale, lack multilingual coverage and focus more on contemporary events. To address thes…

Weakly Supervised Medical Entity Extraction and Linking for Chief Complaints
Zhimeng Luo, Zhendong Wang, Rui Meng, Diyang Xue, Adam Frisch, Daqing He
https://arxiv.org/abs/2509.01899

Weakly Supervised Medical Entity Extraction and Linking for Chief Complaints
A Chief complaint (CC) is the reason for the medical visit as stated in the patient's own words. It helps medical professionals to quickly understand a patient's situation, and also serves as a short summary for medical text mining. However, chief complaint records often take a variety of entering methods, resulting in a wide variation of medical notations, which makes it difficult to standardize across different medical institutions for record keeping or text mining. In this study, we propose …

PRoH: Dynamic Planning and Reasoning over Knowledge Hypergraphs for Retrieval-Augmented Generation
Xiangjun Zai, Xingyu Tan, Xiaoyang Wang, Qing Liu, Xiwei Xu, Wenjie Zhang
https://arxiv.org/abs/2510.12434

PRoH: Dynamic Planning and Reasoning over Knowledge Hypergraphs for Retrieval-Augmented Generation
Knowledge Hypergraphs (KHs) have recently emerged as a knowledge representation for retrieval-augmented generation (RAG), offering a paradigm to model multi-entity relations into a structured form. However, existing KH-based RAG methods suffer from three major limitations: static retrieval planning, non-adaptive retrieval execution, and superficial use of KH structure and semantics, which constrain their ability to perform effective multi-hop question answering. To overcome these limitations, w…

InfoAgent: Advancing Autonomous Information-Seeking Agents
Gongrui Zhang, Jialiang Zhu, Ruiqi Yang, Kai Qiu, Miaosen Zhang, Zhirong Wu, Qi Dai, Bei Liu, Chong Luo, Zhengyuan Yang, Linjie Li, Lijuan Wang, Weizhu Chen, Yuan Zhang, Xin Li, Zhaoyi Liu, Xin Geng, Baining Guo
https://arxiv.org/abs/2509.25189…

InfoAgent: Advancing Autonomous Information-Seeking Agents
Building Large Language Model agents that expand their capabilities by interacting with external tools represents a new frontier in AI research and applications. In this paper, we introduce InfoAgent, a deep research agent powered by an innovative data synthesis pipeline and orchestrated web search tools. To construct challenging, hard-to-find queries,we build entity trees and apply sub-tree sampling with entity fuzzification to systematically increase question difficulty. Unlike prior work tha…

Automated Evidence Extraction and Scoring for Corporate Climate Policy Engagement: A Multilingual RAG Approach
Imene Kolli, Ario Saeid Vaghefi, Chiara Colesanti Senni, Shantam Raj, Markus Leippold
https://arxiv.org/abs/2509.08907

Automated Evidence Extraction and Scoring for Corporate Climate Policy Engagement: A Multilingual RAG Approach
InfluenceMap's LobbyMap Platform monitors the climate policy engagement of over 500 companies and 250 industry associations, assessing each entity's support or opposition to science-based policy pathways for achieving the Paris Agreement's goal of limiting global warming to 1.5°C. Although InfluenceMap has made progress with automating key elements of the analytical workflow, a significant portion of the assessment remains manual, making it time- and labor-intensive and susceptible to human er…

Model-Based Ranking of Source Languages for Zero-Shot Cross-Lingual Transfer
Abteen Ebrahimi, Adam Wiemerslage, Katharina von der Wense
https://arxiv.org/abs/2510.03202 https://…

Model-Based Ranking of Source Languages for Zero-Shot Cross-Lingual Transfer
We present NN-Rank, an algorithm for ranking source languages for cross-lingual transfer, which leverages hidden representations from multilingual models and unlabeled target-language data. We experiment with two pretrained multilingual models and two tasks: part-of-speech tagging (POS) and named entity recognition (NER). We consider 51 source languages and evaluate on 56 and 72 target languages for POS and NER, respectively. When using in-domain data, NN-Rank beats state-of-the-art baselines t…

Joint Modeling of Entities and Discourse Relations for Coherence Assessment
Wei Liu, Michael Strube
https://arxiv.org/abs/2509.04182 https://arxiv.org/pdf/…

Joint Modeling of Entities and Discourse Relations for Coherence Assessment
In linguistics, coherence can be achieved by different means, such as by maintaining reference to the same set of entities across sentences and by establishing discourse relations between them. However, most existing work on coherence modeling focuses exclusively on either entity features or discourse relation features, with little attention given to combining the two. In this study, we explore two methods for jointly modeling entities and discourse relations for coherence assessment. Experimen…

Replaced article(s) found for cs.CL. https://arxiv.org/list/cs.CL/new
[1/5]:
- Medical Question Summarization with Entity-driven Contrastive Learning
Wenpeng Lu, Sibo Wei, Xueping Peng, Yi-fei Wang, Usman Naseem, Shoujin Wang

A Survey on Current Trends and Recent Advances in Text Anonymization
Tobias Deu{\ss}er, Lorenz Sparrenberg, Armin Berger, Max Hahnb\"uck, Christian Bauckhage, Rafet Sifa
https://arxiv.org/abs/2508.21587

A Survey on Current Trends and Recent Advances in Text Anonymization
The proliferation of textual data containing sensitive personal information across various domains requires robust anonymization techniques to protect privacy and comply with regulations, while preserving data usability for diverse and crucial downstream tasks. This survey provides a comprehensive overview of current trends and recent advances in text anonymization techniques. We begin by discussing foundational approaches, primarily centered on Named Entity Recognition, before examining the tr…