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Computation & Language / NLP
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The newest 5,000 papers, from 17 September 2026 to 5 November 2026: 5,000 arXiv preprints.
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Newest papers, page 52
TriageRAG: Failure-Aware Self-Training for Adapting Retrieval-Augmented Language Models to Specialized Domains
Retrieval-augmented generation (RAG) lets large language models (LLMs) answer knowledge-intensive questions from retrieved evidence, but adapting a general-purpose RAG system to a specialized domain…One Scan is Enough: Demonstration-Free Adaptation for Language-Guided Navigation
Deploying a language-guided navigation policy in a new building usually means watching it fail.Whispers from the Neighbors: Rethinking Caption Consensus as Inference-Time Evidence for Vision-Language Retrieval
An image is rarely described only once.MTA-Zero: Self-Improving Multimodal Deep Search via Online QA-Solver Co-training
Multimodal large language models (MLLMs) have become strong visual reasoners, yet remain limited in open-world, multi-step search that requires grounding images, selecting tools, and integrating web…IntentDelta: A Human-Constructed Benchmark for Evolving User Intent
Language-model agents must adapt as users revise their requirements and priorities during complex tasks.Task Format as a Factor in Adaptation: A Controlled Comparison of LoRA and Full Fine-Tuning for Prompt-Safety Classification
Fine-tuning a language model for classification involves many design decisions.EnvLunch: The Environment as a Free Lunch for Learning to Interact
For agentic data analysis, language-model agents often require a large number of annotated tasks to learn how to interact effectively with executable environments (i.e., databases).EdgeDeID: A 0.6B Clinical De-identifier Trained Without Real Patient Data
De-identifying clinical notes with a hosted language model discloses the information the step is meant to protect.Grounding on Request: Learning Modality Control in Vision-Language Models
When an image and its caption disagree, can a user reliably control which one a vision-language model (VLM) follows?Ranking Is Not Deciding: Benchmark Shortcuts and Operating-Point Collapse in Query-Time RAG Poisoning Defenses
Query-time filters that screen each retrieved document before it reaches the generator are the dominant published defense against retrieval-augmented generation poisoning, and they report…Intervention-Certified Amplification: A Validity Gate for $σ$-Weighted Post-Training
Hybrid post-training often mixes supervised fine-tuning (SFT) and reinforcement learning (RL), using training-side signals to set each sample's balance.When Personas Become Harmful: Guiding LLMs with Global Citizenship Values Alignment
LLMs are increasingly being used by users from diverse demographics with pluralistic values and distinct backgrounds.Counterfactual Test-Time Augmentation for Shortcut Removal in Language Models
Large language models (LLMs) can exploit shortcuts, i.e., correlations present in training data that may not hold at test time.HerHealthGPT: An Evidence-Grounded Conversational AI System for Women's Reproductive Health Copy title
"Why is my period late?Schema-Free Text-to-SQL: Learning Enterprise Database Structure from Query Logs
Text-to-SQL systems achieve remarkable accuracy on academic benchmarks, yet performance drops dramatically in enterprise deployments.Why Does Structured Output Fail? An Empirical Study of Prompt-Enforced Pydantic Schemas Across Nine LLMs
Pipelines that require structured outputs from hosted language models often specify a Pydantic schema in the prompt, validate the response, and retry when validation fails.What Makes a Question Curious? Measuring Model Curiosity in Human-LLM Interactions
Large language models increasingly act as partners in everyday communication.CRM-Agent-Bench: Benchmarking Tool-Using Agents in Stateful Enterprise Environments
Deploying language agents in real applications demands more than the right answer: an agent must execute a multi-step business process correctly, follow domain-specific rules, and interact with a…X-Dubbing: Speech-to-Speech Translation under Temporal and Visual Constraints
Cross-lingual dubbing aims to convert source speech into target-language speech that remains synchronized with the original video.How Much Do You Trust A Dog? Quantifying Hint-Following in Reasoning Language Models
Large language models (LLMs) often exhibit sycophancy, altering their answers to align with user suggestions even on objective factual and reasoning tasks.