AI & Machine Learning · Computer Science & AI
Computation & Language / NLP
The newest papers in Computation & Language / NLP that ReadSearch has read, newest first. Each links to its own page, with its authors, date, where it was published and the original.
The newest 5,000 papers, from 17 September 2026 to 5 November 2026: 5,000 arXiv preprints.
Get the few papers worth your time in Computation & Language / NLP every morning.
Follow Computation & Language / NLP and ReadSearch reads its new papers each day, then brings you the few worth reading, each with its key finding in a sentence.
Newest papers, page 81
TRACE: Training-aware Robustness and Challenge Evaluation for Text-Vision Embedding Models
Existing benchmarks for text-vision embedding models report aggregate scores that obscure whether performance comes from general capabilities, task-specific adaptation, or robustness to challenging…How to get the best and fairest performance out of your ASR system using activation steering
Activation steering for ASR systems is an underexplored technique in improving both ASR performance and demographic fairness.Evaluating Tibetan Speech Recognition Across Dialects and Adaptation Regimes: A Multi-Granularity Analysis
Tibetan speech recognition is usually evaluated with character or syllable error rates because the writing system does not mark word boundaries.Decomposed Relation Extraction from Aviation Accident Narratives: Evaluating Transformer-Based Safety Knowledge Discovery under Relational Sparsity
Relation extraction from aviation accident narratives is challenging because genuine safety relations are sparse among possible concept pairs.Teaching AI Agent to Play Poker Strategically Through Preference Optimization
A poker agent can make a legal move and still make a strategically poor one.Fluent but Fallible: Benchmarking Hallucination and Factual Reliability in Large Language Models
Large Language Models (LLMs) have significantly advanced natural language processing and artificial intelligence applications through their capabilities in reasoning, text generation and knowledge…Cross-Lingual Reusability of LLM Pipelines: Financial Extraction, Multilingual Reasoning, and Semantic Screening
Financial institutions increasingly deploy large language models (LLMs) in multilingual markets, raising a practical question: can pipelines developed and validated in English be reused across…ReuF2F: Benchmarking Coding Agents on Formalized Undergraduate Research Problems
As AI systems begin to resolve open research problems, reliable verification becomes increasingly important.Discrete Neural Interlingua for Ontology-Agnostic EHR Modeling
EHR foundation models promise scalable clinical prediction across health systems, yet their deployment is constrained by a tokenization bottleneck.ClockMark: Adaptive and Host-Dependent Watermarking for Large Language Models
Large language model (LLM) watermarking operates on the next-token distribution that evolves during generation.SciFigBench: A Benchmark for Scientific Method Figure Understanding
Scientific method figures often provide researchers with a clear visual entry point into a paper's methodology and core contributions, yet their dense layouts and complex information flows are…Omni-Woodpecker: Hallucination Correction via Evidence-Prior Rebalancing for Omni LLMs
Recent Omni LLMs (OLLMs) have demonstrated remarkable capabilities in joint audio-visual reasoning, yet cross-modal hallucinations remain a major challenge.Beyond Two Tracks: Speaker-Anchored Full-Duplex Dialogue Recovery
Spoken interaction is moving from alternating turns to full-duplex conversation, where an agent listens while speaking.Joint Constraint Aggregation for Qualifier-Sensitive Retrieval-Augmented QA
Retrieval-augmented QA can fail even when the correct answer is in the retrieved evidence.ICLHerd: Herding-Based Data Selection for LLMs with In-Context Learning as a Proxy
Data selection plays a central role in modern large language model training, as the quality of training data strongly influences downstream performance.GRID: Modeling Health Influencer Discourse as Argument Networks for Credibility Assessment
Health-related discussions on social media are increasingly shaped by influencers who offer diverse, and often competing perspectives on the same issue.SITO: Sifting a Commercial Text-Safety API for Missed Harm and False Flags in English, Ukrainian and Surzhyk
Platforms that host young users screen messages with commercial text-safety APIs, but independent evidence on how often such systems miss harm or flag harmless text is scarce, especially outside…On the Fragility of Tasks under Composition: Implicit Budgeting in Language Models
Modern language models are increasingly asked to handle several tasks within a single prompt.Preference-Aware Pareto Steering for Multi-Task Speech LLMs
Speech large language models (LLMs) perform multiple tasks, including automatic speech recognition (ASR), timestamp prediction (TS), and speech translation (ST).The Culture Within: Towards Mechanistic Understanding of Cultural Reasoning in LLMs
Large Language Models (LLMs) increasingly operate across culturally diverse settings, yet existing evaluations largely measure cultural behavior at the output level.