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Newest papers, page 84
Policy Is Not Capability: Some Safety Benchmarks Measure Which Definition of "Unsafe" You Trained On
A guardrail classifier is reported as if unsafe were a property of text.P2N: Reusing Deep Representations for Greater Effective Depth
Mathematical problem solving and autonomous agents are increasingly important applications of language models, demanding stronger reasoning capabilities.CoEvo-RSI: When Harnesses Evolve, Which Models Should Follow?
Model--harness co-evolution has emerged as a prominent paradigm for recursive self-improving (RSI) agents, jointly evolving their execution scaffolds and intrinsic capabilities.Dual-Slot: From Serial Loops to Parallel Slots in Language Models
Looped language models increase computational depth by repeatedly applying shared layers, offering a way to improve model quality without adding parameters.Beyond Factual Accuracy: A Benchmark for Evaluating Perspective Alignment in LLMs
Large Language Models often generate factually correct responses that fail to maintain user-requested perspectives, blending multiple perspectives and forcing users to filter through unwanted…Deep Fusion Memory: A Chunk-Level Parametric Memory for Large Language Models
Large language models need effective ways to acquire and use external knowledge beyond what they retain from pretraining.Generation-Heavy Hybrid Machine Translation
The state of the art techniques in Machine Translation (MT) require large amounts of symmetric resources from source and target languages.Behave Like Experts: Fusing Data with Semantic Knowledge for Effective and Efficient Semantic Map Construction
Semantic map models (SMMs) construct a graph that reflects conceptual similarity by comparing cross-lingual form-meaning mappings.Memories That Outlive Their Reasons: Dependency-Tethered Memory for Tool-Using LLM Agents
Agents now act on the Web, publishing packages, models and datasets through registry APIs, and remembering past verifications spares them the work.Trackable Skill Library Lifecycle Management for Agentic Reinforcement Learning
Skill-augmented agentic RL has emerged as an effective approach to improving LLM agents on long-horizon tasks.MemBubble: Benchmarking How Agent Memory Shapes LLM Response Diversity
Memory serves as the core component of LLM-based agents, enabling personalized responses via extracting and using user preferences from past interactions.TIRE: Top-Down Formula Instantiation with Reliable Execution for Physics Problem Synthesis
Advancing physics reasoning in large language models requires scalable training data that connect physical laws, concrete problem scenarios, and verifiable numerical answers.PLANE: Plug-and-Play Fine-Grained Visual Experts for Hallucination Mitigation in Large Vision-Language Models
Large Vision-Language Models (LVLMs) commonly suffer from hallucinations, which appear as fabricating non-existent objects or outputting incorrect attributes and spatial relationships in images.Morpheus: a fully local, defense-in-depth de-identification engine for Greek clinical text - a benchmark evaluation
Background and Objective: Clinical free text cannot leave the hospital without de-identification, yet no de-identification system or benchmark exists for Greek clinical text.Do LLMs Reproduce the Age Gap in Loneliness? Evaluating Survey Simulation against European Survey Data
Large language models (LLMs) are often used to simulate survey respondents, but matching survey averages does not establish accurate demographic differences.Legal Guidance in the Wild: How Users Seek Legal Help in Real-World LLM Conversations
People ask conversational AI models about their legal rights, obligations, procedures, and personal situations that may have legal consequences.Indistinguishable Agents: Training Agent Privacy as Twin-World Indistinguishability
LLM agents search, shop and send messages for their users, and every action is seen by some party.Memory, Know Your PLACE: Governing Lifecycle State and Query-Time Eligibility in Persistent-Memory Agents
Persistent memory turns prior interactions into durable agent state, but existing systems provide limited control over whether that state remains valid and whether it should influence a later query.Dialogue Generation for Conversational Recommendation Using User Search Interactions and Knowledge Graphs
Large-scale conversational recommendation datasets typically require manual dialogue construction or annotation.Concept Representations in Vector Space: Toward an Interdisciplinary Study of Meaning Variation
An increasing number of disciplines recognize the explanatory potential of meaning-bearing mental structures through which individuals interpret the world and guide their behavior.