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Newest papers, page 110
Gray-Box Hallucination Detection in LLMs with Token Identities
Large language models often produce fluent but factually incorrect output.A Strong Harness Narrows the Model Gap: A Comparative Evaluation for Legislative Document-to-XML Conversion
Legal-content reproduction requires matching the source exactly in section hierarchy, verbatim text, citations, and amendment spans; a dropped citation or mislabeled amendment carries into the…LintEval: Benchmarking LLMs on Linter-Guided File Refactoring
Linters are widely used in code maintenance and real-time IDE editing to surface lint alerts related to performance, style, error-prone, and other patterns in source files.FACES: Fine-grained Gated Semantic Alignment for Multimodal Emotional Support Conversation
In recent years, with advances in multimodal interaction technologies and the growing demand for intelligent emotional support, Multimodal Emotional Support Conversation (MESC) has emerged as an…What Is a Clarification? Estimating Model-Dependent Input Ambiguity
Ambiguous inputs can admit multiple interpretations, each potentially yielding a different answer.Which Knowledge Should LLMs Trust? Uncovering a Generalizable Steering Direction Across Knowledge Conflicts
Large Language Models (LLMs) frequently encounter conflicts between internal parametric knowledge and external contextual knowledge, yet the mechanisms governing this selection remain unclear.Designing Textual Interfaces To Enhance Llm Reasoning On Audio-Visual Question Answering
Automatic prompt optimization (APO) has shown strong effectiveness for text-based LLMs and LLM systems, but its application to audio-visual understanding systems requires suitable textual interfaces…AFCS: Atomic-Fact-Conditioned Synthesis for Factual Knowledge Pretraining
Synthetic data is increasingly used in language-model pretraining.Language Exposure Matters: Distribution and Order in Multilingual BabyLM Pre-training
We investigate two aspects of multilingual pre-training with limited data, namely how language exposure is distributed across English, Dutch, and Chinese, and how that exposure is ordered during…Why Generate a Click? Plug-in Decision Heads for Web Agents
Web agents built on vision language models decide every action by generating text such as click(12), although most of that text encodes a choice among a few action types and a few dozen marked…Sparse Autoencoders for Mechanistic Interpretability in NLP: A Critical Survey of Recoverability, Interpretability, and Utility
Sparse autoencoders (SAEs) have emerged as a promising approach to mechanistic interpretability by decomposing language-model activations into sparse, potentially interpretable features.LLM-Based Policy Compliance Verification of Loan Applications
Banks rely on extensive internal policy frameworks to ensure that corporate lending decisions comply with regulatory requirements and internal risk standards.Gap Detection: Mitigating Homogenization through Demand and Defensibility
Language models often produce semantically similar answers to open-ended questions, even when many plausible alternatives exist.MultiPartyTurnBench: Benchmarking Floor Control in Multi-Party Spoken Dialogue
Full-duplex speech systems must decide when to enter, hold, or relinquish the conversational floor, even as multiple speakers overlap or backchannel without taking it.RM-OPD: On-Policy Distillation for Generative Reward Models
Reinforcement Learning on Mixed-domain preference data (Mix-RL) has become the mainstream approach for training general-purpose Generative Reward Models (GRMs).TreeSpark: Learning to Draft the Trees You Verify for Speculative Decoding
Parallel drafters such as DFlash and DSpark reduce proposal latency, but early mismatches limit how much of each block can be accepted.Cross-Model In-Context Neurofeedback Reveals (Limited) Activation Control in LLMs
Probes on activation vectors are widely used to detect misbehavior in language models, but their success relies on the assumption that models cannot control what their activations encode.When Occupation-derived Skills Don't Help: On the Limits of Skill-Augmented Career Path Prediction
Skills are widely assumed to play a central role in career transitions, motivating their use in career path prediction (CPP) systems.What Makes a Social Agent's Interactions Effective? Learning from Verifiable Outcomes in Paired Worlds
Effective social interaction requires more than fluent responses: agents must reach plans that fit the participants' needs and circumstances.Scaling Multilingual Safety and Reasoning Evaluation through Reasoning-Guided Translation
Large language models (LLMs) are increasingly deployed across languages, yet their safety and reasoning capabilities remain predominantly evaluated in English.