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Newest papers, page 63
A Large-Scale Evaluation of Role-Enhanced Zero-Shot Chain-of-Thought Prompting
This paper proposes Role-Enhanced Zero-Shot Chain-of-Thought (RE-ZS-CoT), a prompting framework that systematically integrates domain-specific expert roles to enhance reasoning in large language…Same Answer, Different Reasons: Trace-Level Divergence in Multilingual Large Language Models
Multilingual large language models are increasingly deployed in settings where visible reasoning traces support verification, education, and safety auditing, yet standard evaluations typically…Multi-level Encoder with Global Topic for Task-oriented Dialogue Summarization
Task-oriented dialogue summarization aims to automatically extract key information to generate domain summaries to improve service efficiency and quality.GRAM: Group-wise Rank-Aware Model Merging via Subspace Alignment
Merging different models into a single model is highly desirable for multi-task deployment, particularly in regulated domains like healthcare.GRAFT: Restoring the Missing Sampling Interface in Continuous Diffusion Language Models
Continuous diffusion language models generate a whole sequence in parallel, never drawing a single word at any intermediate step; only the final step turns embeddings into text.VeeReview: Measuring Build-Verify Pairs in Agent-Authored Pull Requests from a V-Model Perspective
Reviewing a pull request requires verification evidence that addresses the proposed change.Why is AI-generated language so hard to understand?
There is a widespread sense that AI-generated text has recently become harder to understand.Carving Radiology Reports at Their Evidential Joints: Anatomical Region Sets as Generation Units
Organizing radiology reports into independently generated units offers a way to generate fine-grained clinical content and bind it to visual evidence.TeachBack: Learning to Teach via Bidirectional Preference Optimization for On-Policy Self-Distillation
On-policy self-distillation (OPSD) enables a language model to learn from a Teacher instantiated from the same model but given access to privileged information, such as a reference solution.TrainBridge: Agentic NPU Training Optimization Guided by GPU Compilation Evidence
We study how to improve training efficiency on Ascend NPUs.LTEM: LLM-Friendly Table-Enhanced Markdown for Table Understanding and Generation
Tables in real-world documents, including scientific papers, financial reports, and statistical summaries, frequently use merged cells, multi-level headers, and sectioned layouts.Reasoning-Search-Augmented LLMs: An Operational Taxonomy, Benchmark Analysis and Controlled Evidence Synthesis
Large language models (LLMs) demonstrate impressive emergent reasoning capabilities, yet they remain constrained by fixed model parameters and finite context windows.norregel: a preregistered benchmark of dated numeric values in Norwegian law
norregel asks language models for numeric values in Norwegian statutes, regulations and parliamentary decisions (NOK amounts, percentages, multiples of the National Insurance basic amount (G) and…Understanding Target Probability Reuse in Speculative Decoding
Speculative decoding uses a target model to verify a tree of draft tokens in parallel.Preference Is Not Permission: Personalizing the Auto-Purchase Line in Agentic Commerce
Personalized shopping benchmarks ask which item fits the user; we ask how far an agent may commit on that item, and pose learning the individual's auto-purchase line as a task.When Multiple Choices Are Correct: Asymmetric Probability Allocation in Jev and Other Decision Models
Decision models return normalized probability distributions over candidate choices, which downstream applications can use to select among choices.C$^2$U in RAG: Compositional Concept Unlearning in Retrieval-Augmented Generation
Retrieval-augmented generation can expose unwanted concepts through retrieved evidence even when the generator is moderated.Beyond Binary Labels: Diagnostic Evaluation of LLM Safety with Prompt-Level Rubrics
Current LLM safety benchmarks predominantly rely on binary safe or unsafe labels, lacking explanatory depth and suffering from low consistency across automated judges.MOSAIC: An Omni-Modal Benchmark for Long-Term Memory and Cross-Modal Reasoning in Conversational Agents
Omni-modal assistants must remember not only what users say, but also what they show and convey.Let Agents Design How They Search: Automatic Interface Optimization for Agentic Search
Agentic search depends on the interface through which a language-model agent accesses and explores a corpus.