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Computation & Language / NLP
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Newest papers, page 42
SkillMem: Compact External Skill Memory for Latent Multi-Agent Reasoning
Latent multi-agent systems reduce inference cost by keeping intermediate reasoning and inter-agent communication in continuous representations.\ Reusable skills, however, are commonly supplied as…QMUL_AK at AISA-ArabicFC: Schema-Constrained Function Calling with ALLaM
We describe the QMUL_AK submission to AISA-ArabicFC 2026."It Would Make a Geordie Feel at Home": Regional Accent Perceptions and Speech Accommodation in Voice AI
Automatic speech recognition (ASR) systems often perform less accurately for speakers of regional dialects, but less is known about how users respond to these limitations and how regional voices…Large Language Models for Accurate Medical Chart Abstraction: Enabling Scalable and Secure Artificial Intelligence Deployment in Stroke
Medical chart abstraction transforms unstructured clinical narratives into structured variables for research and quality monitoring.Measured or Real? When Model-Derived Measurements Can Be Corrected or Compared
Numbers computed from trained models, such as an example's difficulty or a model's benchmark lead, change with seed and prompt.Beyond Aggregate WER: In-domain Adaptation, Learner Speech, Code-Switching, and Speaker Attribution in Online Spanish Learning Classrooms
Automatic speech recognition (ASR) increasingly supplies transcripts for educational NLP, but aggregate word error rate (WER) can conceal errors concentrated in learner speech, multilingual turns…CARF: Context-Aware Reasoning Supervision for Scientific Evidence Screening
Systematic reviews synthesize biomedical evidence to inform clinical and public-health decision-making, but require domain experts to manually screen thousands of studies against detailed…From Error Prediction to Causal Influence: Auditing SAE Features in Multiple-Choice QA
Sparse autoencoders (SAEs) can predict internal features associated with model errors, but association alone does not establish causal influence.Prompt Lottery in LLM-as-a-Judge: Measuring and Mitigating Sensitivity to Syntactic Rephrasing
LLM-as-a-Judge has become a standard for evaluating large language models, yet most approaches implicitly assume that a single judge prompt functions as a stable evaluation instrument.Heard Enough to Act: Early Tool Calling in Spoken Dialogue Systems
Latency-sensitive spoken agents must know not only which tool to call, but also when they have heard enough to act.AdaTutor: Adaptive Tutoring through Pedagogical Strategy Selection
Effective tutoring requires determining not only what information to provide, but also which form of assistance to deliver.Agent Memory as Recommendation: Recommender-System Design for Long-Term Memory of LLM Agents
Large language model (LLM) agents that serve users across many sessions must choose, for every request, the few stored memories that enter a limited context window.Knowing When the Evidence Is Enough: Requirement-Directed Search with Horn-Closure Certificates
After each Web search, a search-augmented model must decide whether its evidence suffices: answer, search again, or abstain.iPrefBench: A User-Centric Benchmark for Personalized Mobile Use Agents
An agent that truly knows and acts on behalf of its user has been a long-standing promise of AI assistants.LADDER: Diagnosing Domain-Level Self-Assessment Under Noisy Feedback
Knowing when they are reliable is essential for language models to support human-AI collaboration.DecisionTraceBench: Tracking Decision-Critical Information in Multi-Party Spoken Conversations
In high-stakes domains such as finance, critical information evolves through multi-party interaction.Mechanistic Insights into LoRA: Layer Sparsity for Adaptive Fine-Tuning via Path Patching
Low-Rank Adaptation (LoRA) has emerged as the dominant paradigm for parameter-efficient fine-tuning of large language models.From Belief Inference to Task Action: A Multi-Level Evaluation of Theory of Mind on Verifiable Tasks
Effective collaboration requires language models to understand what others know and believe, and to act accordingly.DynEdit: Dynamic Entropy-Guided Sequential Editing for Large Language Models
Knowledge editing aims to update outdated or incorrect knowledge in large language models without full retraining.Natural Jammers: When Non-Robust Features Become Antagonistic
Deep neural networks are known to rely on non-robust features that align poorly with human perception.