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Newest papers, page 93
Robust Function Calling for LLM Agents Under Interface Drift
Tool-augmented language-model agents rely on interface text: tool descriptions, argument schemas, and the candidate tool list shown at inference time.Language Models Learn to Improve Language Models
Large language models (LLMs) are increasingly used to automate AI research, including language-model (LM) development, offering a potential path toward recursive self-improvement.Sentence-Level Topic Modeling with Lexical and Contextual Evidence
Topic modeling faces a fundamental granularity dilemma: probabilistic topic models assign topics at the word level, whereas transformer-based methods operate at the document level.On the Tip of the Tongue: First-Token Cueing as a Behavioral Probe of Recall Failures in LLMs
Large language models often answer factual questions incorrectly in closed-book settings, and such errors are usually attributed to missing knowledge.ScoutRoute: Efficient Mixture-of-Experts Routing Using Internal Language Model Signals
Efficient expert routing is a fundamental challenge in Mixture-of-Experts (MoE) systems, particularly for heterogeneous collections of independently trained Large Language Mod els (LLMs)."You" Is Not Toxic: How LLM Labelers Rewrite the Web's Conversation Laws
What the Web community believes about toxic conversations, such as that toxicity rises in longer and deeper threads, was measured mostly with Google's Perspective API, which is shutting down; large…HydraLLM: Adaptive Width Slicing for Elastic Text and Vision-Language Models
LLMs and LVLMs are increasingly deployed across heterogeneous hardware, ranging from data-center GPUs to resource-constrained edge devices.A low-dimensional dynamical basis for tongue shape control
Speech production involves the control of a high-dimensional articulatory system with many degrees-of-freedom, but a widespread hypothesis is that speakers navigate this complexity using a set of…MuninAI: A Self-Hosted Agentic Framework for Independent Research Groups
Research groups that want a language model grounded in their own literature face a choice between hosted services that receive their unpublished work and self-hosted deployments that keep the data…Perceive, Solve, Reason: Progressive Capability Formation in Time Series-LLMs
Large language models (LLMs) can now perceive, describe, and reason about images and audio, yet time series understanding remains underestimated: most work uses LLMs as forecasters and classifiers…Truth in Contrast: Calibrated Factual Evidence from Language Model Likelihoods
Large Language Models (LLMs) encode substantial factual knowledge.EduWild: How Teacher-Configured Chatbots Fail in Real-World Use and How to Fix Them
Teachers increasingly configure educational chatbots through natural-language instructions, but how these bots fail in real-world use remains poorly understood.ConvexLLM: Scaling Convex-Hull Speech Interfaces to General-Purpose Audio Intelligence
Speech and audio language models connect continuous acoustic representations to decoders pretrained primarily on text data.Execution Before Memory: Diagnosing Memory Failures in Video World Models
A memory test for a video world model should say whether the scene was set, whether the asked change was carried out, and whether the last frame shows the result.MARS: Memory-Aware Routing for Session-Level LLM Assistants
Long-term LLM assistants must repeatedly decide what prior context to expose and which model should answer as an interaction evolves.Analyzing Occupational Gender Bias across the LLM Training Lifecycle
Post-training is widely assumed to reduce the social biases language models inherit from pretraining, yet direct evidence for this assumption remains mixed.Enhancing RAG-based Medical VQA with Gated Multimodal Representations
Medical Vision-Language Models (Med-LVLMs) have shown strong performance in Medical Visual Question Answering (MVQA), yet they may still produce factually inconsistent responses.Not Every Mention Is a Claim: Rethinking Object Hallucination Detection in Vision-Language Models
Object hallucination in vision-language models (VLMs) is usually measured by checking each object a caption names against the image.SIT-Eval: Situation-Based Interactive Turn-by-Turn Evaluation of Conversational Agents
The rapid proliferation of conversational AI agents necessitates evaluation methods that assess performance across diverse dialogue scenarios, utilizing multiple situational criteria, as appropriate…Trajectory-Triggered Sparse Collaborative Decoding
Dense assistance methods such as speculative decoding repeatedly verify draft tokens with a target model, keeping target computation coupled to generation.