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Newest papers, page 168
IREA: Intermediate Representation-based Embedding Alignment for Normative RAG
Large language models (LLMs) have shown strong performance across various tasks, but they still struggle with questions involving ethical judgment.When LLMs Sit Above Diagnostic Tools: Unrealized Complementarity in Industrial Fault Diagnosis
Large language models are increasingly used as integration layers above specialized tools, but a stronger component does not necessarily produce a stronger combined system.Causal Improvement Graph for Agentic Harness Optimization
Agentic Harness is the runtime that constructs task context and controls execution flow, thereby shaping overall agent performance.Communication Shapes Collective Inference in Self-Adapting LLM Societies: Evidence from Mafia
When does communication help a group identify hidden adversaries, and how does its value change as the group adapts?AraYoungVoices: A Diverse L1/L2 Corpus of Arabic Child and Adolescent Speech
State-of-the-art ASR systems primarily target native adult speech, leading to substantial performance gaps for children, adolescents, and L2 speakers.Usage-Modulated Sentiment Representations in Large Language Models
Prior work suggests that sentiment can often be captured by approximately linear directions in LLM activation spaces, but a single direction may not fully capture sentiment representations.Self-Generated Feedback Destabilizes Test-Time Training: A Causal Decomposition of Long-Horizon Adaptation
Test-time training (TTT) lets a model store information in its weights during inference.Towards cross-cultural study of folksong lyrics with machine translation
Music is universally present in human societies.How Much Do LLM-as-a-Judge Design Choices Matter? A Systematic Comparison of Prompt Designs, Rating Scales, and Models
Researchers increasingly use Large Language Models as judges (LLM-as-a-judge) to evaluate model outputs.vMF Sentence LDA: A Spherical Topic Model over Sentence Embeddings
Latent Dirichlet Allocation (LDA) and models derived from it remain widely used topic models.ReMAP: Restoring the Perceptual Cycle with Reasoning-Time Latent Visual Memory
As multimodal large language models (MLLMs) reason for longer, attention to the initial visual input diminishes, weakening visual grounding.Small Agents with Semantic Search: Efficient Multilingual Code Localization
Locating relevant files from natural-language requests is a core subtask for agents operating over code repositories.SearchJev: A Fast and Calibrated System-1 Model for Search Agents
Search agents repeatedly make short decisions about relevance, evidence sufficiency, and search actions.InstMoE: Adaptive Multimodal Routing with Specialized Experts
Multimodal inputs are inherently heterogeneous, not only across modalities but also in the information pathways required for effective prediction.Belief-Trajectory Energy: Measuring the Path to a Prediction
Large language models (LLMs) progressively revise their predictions across Transformer layers, yet we typically observe only the final output, discarding the trajectory through which it is formed.Selecting Repetition Counts Across Model Scales in Data-Constrained Pretraining
The repetition count that works best for a small language model may not remain best at a larger scale.Verification Trap: Understanding Test-Time Selection Failures under False Premises in Code Generation
Test-time compute has become a central way to improve code generation: systems sample multiple candidate programs and use verifier-visible evidence to select the final output.FORGE: Verification-Gated Behavioral Repair for Generative Language Models
Generative large language models (LLMs) inherit undesirable behaviors from pre-training, including demographic bias and toxic generation, that often emerge only after deployment and affect a small…Safe Context Switching for Agents in the Wild: Mitigating Subspace Interference via Orthogonal Adaptation
Most Large Language Models exhibit a fundamental tension between two sequential tasks, such as logical reasoning and safety alignment.Look Before You Leap: Thermodynamic Arbitration of Parametric and Non-Parametric Knowledge in LLM Agents via Self-Regulating Memory Architectures
The architecture of modern LLMs consists of a profound cognitive polarization.