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natural language processing

9,568 papers

#natural language process... Preprint Open access Oct 2026

Where Did We Go Wrong? Localizing Errors to Repair Multi-Turn Conversations

Large language model (LLM) assistants are increasingly used in multi-turn conversations, where the user's intent is often unclear at first and revealed only gradually over time. The assistant must therefore interpret each exchange and form inferences about the user's intent, using them to update its working state. Thes...

Alessandro Morosini, Wei Sun, Georgia Perakis · 0 citations
#natural language process... Preprint Open access Oct 2026

Lumen-bench: Cross-Lingual Safety Gaps and the Say-Do Problem in Tool-Calling Large Language Models

When a large language model refuses an unethical request, what does refusal mean? In conversation, refusal is bounded by what the model says; once the model is equipped with executable tools, what it does can diverge from what it says, a failure mode that English-only evaluations cannot fully reveal. We introduce Lumen...

Giovana Kerche Bon\'as, Thiago Laitz, Thales Sales Almeida et al. · 0 citations
#natural language process... Preprint Oct 2026

RegExtract: A Benchmark for PFAS Regulatory Information Extraction with LLMs

RegExtract is introduced, a benchmark for structured information extraction from PFAS regulatory documents, comprising 488 human-annotated field instances across 20 US state documents and 46 regulations, and a typed, multi-field schema targeting key elements such as material definitions, permitted uses, and product exe...

Defne Çirci, Krystelle Lionti, Sarathkrishna Swaminathan et al. · 0 citations
#natural language process... Preprint Oct 2026

PAT: A Personality-Driven Augmentation and Transfer Learning Framework for Depression Detection on Social Media

Depression is a prevalent mental disorder that affects millions worldwide, with early detection crucial for effective intervention. While exist?ing methods have achieved promising results in automated depression detection, they face two key limitations: (1) noise in post screening: symptom-based semantic screening is e...

Shen Zheng, Yu-Zhe Ding, Xiao-Hui Liang et al. · 0 citations
#natural language process... Preprint Oct 2026

Do Personalized LLMs Need the Whole Conversation? Matching the Full History with Only 5% of Its Text via Relevance-Filtered Context

Personalized assistants accumulate long conversation histories, and passing the whole history to an LLM with every request is costly. We show that it is also unnecessary. On PersonaMem-v2 (180 questions), with GPT-5.6-terra and Claude Opus 5.5 as judges, a relevance-filtered context, built by sentence-level retrieval t...

Eri Hayashi, Andrew Shin · 0 citations
#natural language process... Preprint Oct 2026

FidelityQ: Preserving Predictive Fidelity in Ultra-Low-Bit Language Model Quantization

Ultra-low-bit scalar quantization offers a regular arithmetic structure for efficient deployment of large language models, but preserving predictive behavior at extreme precision remains challenging: with only a few reconstruction levels, accurate weight representation must translate into consistent predictions from a...

Yu-Jie Chen, Wei-Yan Zheng, Yi-Wu Yao et al. · 0 citations
#natural language process... Preprint Oct 2026

TeachGrade: Training-Free Short Answer Scoring with Teacher Evidence

Multi-subject, multi-step scoring requires consistent partial credit across grading conventions. We introduce TeachGrade, a training-free framework using teacher-graded examples. The Task Adapt module builds two frozen memories: Skill captures contextual teacher preferences beyond the rubric; CaseBank supplies local ev...

Jin-Hao Yan, Zhi-Hong Shen, Sheng-Jie Wang et al. · 0 citations
#natural language process... Preprint Open access Oct 2026

Agent-Guided Evidence Acquisition for Emotion-Cause Pair Extraction

Emotion-Cause Pair Extraction (ECPE) requires identifying the causes associated with emotions expressed in a conversation. Accurate extraction can depend on evidence that is not initially available, making it important to decide when further information is worth acquiring. We study agent-guided evidence acquisition for...

Zhuangzhuang Pan, Yan Xia, Chee Seng Chan · 0 citations
#natural language process... Preprint Oct 2026

Social Bias in Chinese Large Language Models under Social Media Expressions

It is demonstrated that expression form is not a transparent carrier in bias evaluation and that lower scores under sarcasm should not be interpreted directly as bias mitigation, and the proposed paired design offers a measurement approach for Chinese social-media contexts while also revealing the construct boundary an...

Zhou Mo · 0 citations
#natural language process... Preprint Open access Oct 2026

Training-Free BioNEL-RAG: Advancing Biomedical Entity Linking through Retrieval-Augmented Generation and Large Language Model

Biomedical Named Entity Linking (BioNEL) is the task of mapping mentions extracted from biomedical texts to canonical entities or concepts in the standardized knowledge base. Although existing methods have achieved remarkable performance in mapping accuracy, most rely on training with domain-specific datasets, which fu...

Ziyi Chen, Hui Liu, Ziyang Ling et al. · 0 citations
#natural language process... Preprint Oct 2026

Who Receives Respect? A Counterfactual Benchmark for Honorific Allocation Bias in Bengali

Bengali has no grammatical gender, but honorificity is obligatory: every third-person reference must choose ordinary or respectful register. English has no such signal, so the system must choose a level of deference that the source never specified. We use this property to measure how large language models (LLMs) alloca...

Ajwad Abrar, Md. Kamrul Hasan, Hasan Mahmud · 0 citations
#natural language process... Preprint Open access Oct 2026

The Constitution Speaks Nheengatu: An Open MT System and Reproducible Corpus Pipeline for the Amazonian L\'ingua Geral

Nheengatu (yrl), the Amazonian L\'ingua Geral, has 6--10 thousand speakers and is co-official in S\~ao Gabriel da Cachoeira (Brazil), yet remains poorly served by evaluated Portuguese--Nheengatu MT resources. We present the largest parallel corpus assembled for the language (14.5k Portuguese--Nheengatu pairs), anchored...

Fabr\'icio Carraro, Rodolfo Joel Zevallos, Rodrigo Gon\c{c}alves de Souza et al. · 0 citations

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Microsoft Research Blog Oct 22, 2026

Flint-interactive: A language for creating interactive data visualizations

Flint-interactive gives AI agents a language for creating interactive visualizations. Click a chart, filter data, highlight related content, and explore beyond the view the author originally chose. The post Flint-interactive: A language for creating interactive data visualizations appeared first on Microsoft Research.

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