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Newest papers, page 207
LLMs as Adaptive Meta-Solvers: Strategy-Diverse RL for Industrial-Scale Optimization
Scaling LLM-based optimization from textbook-scale instances to real-world, industrial tasks remains a critical open challenge.AgentHop: A Diagnostic Benchmark for Agentic Multi-Hop Scientific Question Answering
Agentic tasks require a large language model to interact with the world, navigating information and gathering evidence across multiple steps with restricted resources.Remember by Asking: Retrieval-Induced Memory Evolution for LLM Agents
Long-term memory is essential for language agents to maintain coherent and effective behavior over extended, multi-session interactions.Unbiased Top-$k$ Estimation for On-Policy Distillation
On-policy distillation (OPD) is becoming an important component of large language model (LLM) post-training for transferring the reasoning capability of a strong teacher LLM to a weaker student LLM.When Words Fall Short: Iterative Synergy Between Verbalized Reasoning and Hidden Features for LLM Confidence Estimation
Confidence estimation is crucial for developing trustworthy large language models (LLMs), with most methods following estimator-based or verbalization-based paradigms.RGDT-Bench: Benchmarking LLM Reasoning for Rule-Governed Decisions and Their Justifications
We study reasoning in Rule-Governed Decision Tasks (RGDTs), where models apply external rules to case facts and justify decisions, as required in policy, contract, and compliance settings.The Last Mile Is the File: OfficeEditBench for Preservation-Aware Office Editing
A small Office edit creates two obligations: propagate every required update and leave protected state untouched.CARDAMOM: A Micro-Dialectal Arabic Speech Dataset for ASR
We present Cardamom, a micro-dialectal Arabic speech dataset designed to support fine-grained evaluation and adaptation of automatic speech recognition (ASR) systems.Low-Confidence Remasking Traps Flexibility: Realizing Arbitrary-Order Potential for Diverse Rollouts in Diffusion LLMs
Masked diffusion language models support arbitrary-order generation, suggesting a natural way to produce diverse outputs.How to Tame a Multi-Headed Hydra? Adaptive Multi-Category Safety Steering for Large Language Models
As large language models (LLMs) become increasingly widespread, preventing unsafe responses to harmful prompts is essential for their safe deployment.Papers Without Code: Availability of GitHub Repositories Linked in *CL Publications
Source code and data published at computational linguistics (*CL) venues are increasingly being shared via GitHub.ActionLens: Diagnosing Spatial-Temporal Binding Failures in Vision-Language Models
Video-capable vision-language models score above 80\% on popular benchmarks yet struggle with spatial-temporal binding: associating the right action with the right person at the right moment.RoPE is Dead, Long Live RoPE: Towards Scalable Data-aware Positional Encodings
Transformers process tokens without any inherent notion of order, making positional encoding a fundamental requirement rather than an architectural refinement.Rethinking Latent Visual Reasoning: Grounding Latent Reasoning in Visual Evidence
Latent visual reasoning (LVR) enables multimodal large language models (MLLMs) to perform intermediate computation in continuous latent tokens rather than expressing every reasoning step in words.Nudgeability: Reasoning Models Follow Confidence Signals Without Tracking Their Own Competence
Reasoning language models that can call tools must decide during inference whether to answer unaided or delegate.In-game Toxic Detection: Bi-directional Representations with Attention Residuals
In-game toxic language has emerged as a critical concern in the gaming industry and community.The Model Knows When to Stop: Training-Free Early Stopping for Long-Context Reading
Language models often process long inputs sequentially in chunks, but continuing to read after sufficient evidence has been acquired wastes computation.After the Fix: Transfer of Corrected Agent Experience
Does repairing an episode make its experience a better memory for the next task?When Can Attention Heads Be Statically Defined?
Some attention heads learn similar patterns across inputs.Rewarding Novel Deductions: Solver-guided Process Rewards for Logical Reasoning
Logical reasoning remains a major challenge for large language models (LLMs), particularly on structured problems that require precise constraint tracking, consistency preservation, and multi-step…