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Computation & Language / NLP
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Newest papers, page 98
FGSS-BO: Feedback-Guided Hypothesis Management for LLM-Based Bayesian Optimization
Large language model (LLM)-guided Bayesian optimization (BO) uses past observations to guide search, but proposed directions and their revision can remain implicit.LLM-Based Weak Annotation for Cybersecurity Tweet Classification: A Teacher-Student Framework
Cyber threat intelligence (CTI) relies on the timely identification of emerging threats, enabling organizations and security analysts to support situational awareness and decision-making.Isolating a Language Model's Judgment with a Label-Free Subspace
Language models are often asked to make judgments: whether a proposed answer is correct, whether one statement follows logically from another, or whether a response is safe.Behavioral Compositionality of Sparse Autoencoder Representations
Sparse autoencoders (SAEs) represent model activations with sparse, linearly decoded features, but the downstream effects of those features need not compose additively.TRACER: Trajectory-Aware Tool Retrieval for LLM Agents
Modern agents select tools from registries, but exposing entire registries incurs high token costs and can impair selection as they grow.Auditing Escalation Reliability in Healthcare LLM Agents: A Perturbation-Controlled Benchmark of Workflow-State Failures
Trustworthy biomedical AI requires reliable action selection when evidence is missing, stale, conflicting, or late, not only accurate answers on static inputs.TimeCap: A Scalable Open-Source Pipeline for Captioning Wearable Health Time-Series Data
Time-series data generated continuously across industrial, environmental, and especially health domains produce multimodal signals whose scale and heterogeneity make their processing and…Bias Control and Injection for Multi-Agent Aggregation
Multi-agent reasoning with large language models (LLMs) raises a central question for collective decision-making: when agents disagree, whose decision should be trusted?Making every stage of medical device document assessment with large language models deterministic
To show that a medical device complies with regulation, experts judge whether documents and records meet each requirement and record the judgment for others to verify.VALCON: Benchmarking and Enhancing Value Consistency in Large Language Models via Dual-Role Variation
Current value alignment evaluations for large language models (LLMs) heavily rely on output compliance, overlooking whether LLMs maintain value consistency when alternating between generator and…PocketTSLM: Deploying an On-Device Soft-Prompt Time-Series Language Model for Privacy-Preserving Smartphone Reasoning
Consumer phones and wearables increasingly collect physiological time-series data, yet most mobile systems treat these streams as summaries or text rather than as temporal evidence.ZoomCap: Evidence-Routed Visual Zooming for Recoverable Visual Information Transfer
Detailed captions transfer visual information into vision-language model supervision, but quality is easily conflated with length: long single-pass outputs still miss small objects, text, and…DocPilot: Interactive Agent Orchestration and Training for Long Visual Document Understanding
Multimodal long-document question answering requires models to seek sparse evidence across pages and modalities, understand heterogeneous document content, and reason over the collected evidence.Hybrid Generative-Tagging Decoding for Efficient Product Attribute-Value Extraction
Attribute-value extraction is important for building high-quality product catalogs in e-commerce.VoteGEO-Bench: Measuring the Impact of Generative Engine Optimization on Electoral Visibility
Large language models (LLMs) are increasingly used for election information, yet little is known about how external web content shapes the political information they present.QuasiLeak-Bench: Evaluating LLM-Based Privacy Detectors on Policy-Conditioned Quasi-Evidence Group Recovery
Natural language messages often contain quasi-identifiers that are weak in isolation but can jointly reveal an individual's private attributes.Ranking and Partitioning of Attention Heads for Sparse and Continual Reinforcement Learning Fine-tuning
We study sparse and continual reinforcement learning fine-tuning of language models through attention-head ranking and partitioning.OpCredit: Operation-Aware Policy Learning for Agentic Knowledge Graph Question Answering
Agentic knowledge graph question answering(KGQA) relies on sequences of executable operations, but trajectory-level rewards obscure their individual contributions.Emotion Is Not External Knowledge: Internal Attention Signals for Affective State Reasoning
Large Language Models (LLMs) increasingly operate in multi-turn interactions that require maintaining latent conversational states, not only explicit facts.RenoLayout: Unified Floorplan Renovation and Furniture Layout for Constraint-Aware Residential Design
Residential design aims to transform existing homes into functional living spaces while satisfying diverse design preferences and physical constraints.