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Newest papers, page 184
Acmite: Mitigating Gender Bias in LLMs through Concept-Guided Mutual Information
Large language models (LLMs) can reproduce social stereotypes from their training data, motivating extensive research on model debiasing.Task-Oriented Rank Adaptation for Continual Learning in Text Classification
Continual learning (CL) in text classification faces two critical challenges: catastrophic forgetting and negative transfer across sequential tasks.A Matryoshka Hierarchical RAG for Efficient Multi-Hop Question Answering
Retrieval-Augmented Generation (RAG) systems for multi-hop Question Answering (QA) must balance retrieval quality with computational cost.VETO: Video Efficient Token Optimization for Vision Language Models
Processing long videos with Vision-Language Models (VLMs) is bottlenecked by the quadratic cost of visual tokens, making long-form inference prohibitively expensive.A Safe Prototype Is Not a Safety Direction: Reference Dependence and Prompt Confounds in Response-Safety Embeddings
Can response safety be scored by cosine similarity to the mean embedding of known-safe responses?Beyond Linear Concepts: Discovering and Aligning Non-Linear Concept Manifolds in Large Language Models
Understanding information processing in large language models (LLMs) requires dissecting the geometric organization of their internal token representations.The Asymptotics of Language Model Alignment with Memory
Language model (LM) alignment broadly aims to perturb a given LM $Q$ into an aligned LM $q$ such that i) the outputs produced by $q$ and $Q$ are 'close' in probability, ii) $q$ has a higher expected…Beyond Decodability: Do Acoustic Factors Drive Predictions in Speech-Based Alzheimer's Assessment?
Speech-based Alzheimer's disease (AD) assessments increasingly rely on pretrained self-supervised learning (SSL) models that learn acoustic representations directly from raw audio, exposing the…Detecting Inconsistencies in Model Specifications with LLM-as-Verifier Reasoning
Model specifications define how large language models (LLMs) should behave, guiding alignment training, inference-time behavior, and evaluation.Where LLMs Fail with Visualization DSLs
As LLMs take up the role of authoring charts using visualization domain-specific languages (DSLs), the human constraints that shaped those languages may no longer apply, as what is easy for a person…Stochastic Rounding in Low-Precision Transformer Inference: A Variable-Precision Emulation Study of a Small GPT-2
Should low-precision transformer inference use stochastic rounding (SR) or round-to-nearest (RN)?MoLE: Mixture of Latent Experts for Complementary Visual Reasoning
Latent visual reasoning equips vision--language models with continuous intermediate states that can process visual evidence without explicit textual reasoning traces or repeated image operations.Cross-Lingual Alignment for Decoder-Only Models using MoE Routers
Cross-lingual contrastive learning has been a core component of multilingual encoder training, but the ability to explicitly align representations is not possible in decoder-only LLMs because of…A rubric landscape for evaluating clinical reasoning in large language models: what exists, what is missing, and what needs to be combined
Exam-style accuracy does not establish whether large language models (LLMs) reason well over clinical records.Latent JEPA: Abstract Future Prediction for Latent Reasoning in Chemistry
Large language models offer a promising foundation for chemical reasoning, bringing together chemical knowledge and multistep problem solving.Counterfactual Auditing of Bias in Open-Source Large Language Models for Clinical Triage
Emergency department (ED) triage is a high-stakes prioritization task in which demographic, socioeconomic, and system-context information may improperly influence acuity assignment.Universal Byte-Level Encoding: UTF-8/UTF-16 Routing to Reduce Cross-Script Token-Budget Disparities
Byte-level byte-pair encoding (BBPE) tokenizers are attractive for multilingual large language models (LLMs) because they cover all Unicode text.Mingbird: A Local-First Agent Harness Enabling Small Open Models to Complete Real Tasks
Small open-weight models (2-9B) run on ordinary laptops, but under cloud-scale agent harnesses they rarely complete real tasks: tool prefill overflows the context, self-correction diverges, tool…Mem++: Non-Destructive Memory for Long-Term Organizational LLM Agents
Large Language Model (LLM) agents now take part in organizational work, where many authors record decisions across documents over months.Controllable Multi-label Video Safety Detection via Adaptive Tversky Policy Optimization
The rapid growth of video-based social media has increased users' exposure to harmful content, creating a need for reliable automated video safety detection.