arXiv AI
Oct 1
Hierarchical Reasoning Model
arXiv:2506.21734v4 Announce Type: replace Abstract: Reasoning, the process of devising and executing complex goal-oriented action sequences, remains a critical challenge in AI. Current large language...
Benchmarks and evaluation
Leaderboards, eval harnesses and ablations — the contested business of deciding which model is actually better.
arXiv AI
Oct 1
MedRECT: A Bilingual Medical Reasoning Benchmark for Error Correction in Clinical Texts
arXiv:2511.00421v2 Announce Type: replace-cross Abstract: Large language models (LLMs) show promise in medical applications, but their ability to detect and correct errors in clinical texts remains u...
arXiv Computation and Language
Oct 1
Sequential Bayesian Evaluation of Large Language Model Behavior
arXiv:2511.10661v2 Announce Type: replace Abstract: It is increasingly important to evaluate the characteristics of systems based on large language models (LLMs). Evaluations in this context often re...
arXiv Computer Vision
Oct 1
Overconfidence and Calibration in Medical VQA: Empirical Findings and Hallucination-Aware Mitigation
arXiv:2604.02543v2 Announce Type: replace Abstract: As vision-language models (VLMs) are increasingly deployed in clinical decision support, more than accuracy is required: knowing when to trust thei...
arXiv AI
Oct 1
STEPS: Selective On-Policy Self-Distillation for Reasoning
arXiv:2605.10194v2 Announce Type: replace Abstract: On-policy self-distillation (OPSD) uses a model as its own teacher under privileged context, providing token-level supervision on the model's own r...
arXiv AI
Oct 1
Generalizing the Turing Test to Interactive Agents
arXiv:2605.10851v2 Announce Type: replace Abstract: We initiate the study of the Generalized Turing Test (GTT), a formal generalization of Turing's imitation game from humans to arbitrary interactive...
arXiv Computer Vision
Oct 1
Structure over Pixels: Learning Variable-Length Visual Programs
arXiv:2605.27696v3 Announce Type: replace Abstract: Discrete visual tokenizers map images to ordered sequences of tokens, providing a natural representation for structural scene descriptions. Most us...
arXiv AI
Oct 1
Flow Annealing Posterior Sampling for Function-Space Regression and Inverse Problems
arXiv:2606.22346v2 Announce Type: replace-cross Abstract: Principled regression for stochastic processes is a long-standing challenge with deep connections to scientific inverse problems. We introduc...
arXiv AI
Oct 1
Prefill-Free Cross-Family KV Cache Transfer for Heterogeneous Multi-Agent LLMs
arXiv:2609.32259v2 Announce Type: replace Abstract: Recent multi-agent LLM systems increasingly combine heterogeneous models for specialized agent roles. However, text-based communication requires ea...
arXiv Computation and Language
Oct 1
Large Language Models are Approximate Survival Estimators
arXiv:2609.38181v1 Announce Type: new Abstract: Survival analysis estimates time-to-event outcomes from patient covariates and is widely used for medical risk assessment. Patients seeking prognostic...
arXiv Computation and Language
Oct 1
Evaluating Whether LLMs Can Reliably Connect the DOTs?
arXiv:2609.38406v1 Announce Type: new Abstract: Access to real-world information is often noisy and fragmented. Constructing a coherent narrative from such fragments requires models to reconstruct mi...
arXiv Computation and Language
Oct 1
DEdit: Iterative Draft Editing for Speculative Decoding
arXiv:2609.38510v1 Announce Type: new Abstract: Speculative decoding accelerates autoregressive LLMs by having a lightweight drafter propose tokens that the target model verifies in parallel. Diffusi...
arXiv Computation and Language
Oct 1
Overlap, Unique and Conflict: Can LLMs Extract What They Can Recognize?
arXiv:2609.38799v1 Announce Type: new Abstract: Understanding multi-perspective alternative narratives requires identifying how their information agrees, conflicts, or differs across sources. Existin...
arXiv Computation and Language
Oct 1
A Missing Piece for Trustworthy AI Reviewers: From Benchmarking Rhetorical Robustness to SciCore Review
arXiv:2609.39027v1 Announce Type: new Abstract: AI reviewers can assign different judgments to manuscripts that report the same science in different wording, potentially rewarding rhetorical optimiza...
arXiv Computation and Language
Oct 1
Argument Structure Prediction in Online Conversations: A Comparative Study of Modeling Paradigms and Task Architectures
arXiv:2609.39225v1 Announce Type: new Abstract: Argument structure prediction (ASP) constructs complete argument structures from discourse by identifying argumentative units and their relations. Whil...
arXiv Computation and Language
Oct 1
Offline Guidance, Online Reasoning: Reusing LLM Feedback for Small Language Models
arXiv:2609.39346v1 Announce Type: new Abstract: Large language models (LLMs) offer strong reasoning capabilities but are often costly to access through commercial APIs, while small language models (S...
arXiv Computation and Language
Oct 1
DuplexAct-Bench: Broadening Full-Duplex Speech Evaluation toward Proactive Interaction across Diverse Behavioral Requirements
arXiv:2609.39446v1 Announce Type: new Abstract: Existing full-duplex speech benchmarks cover only subsets of real-time interaction behaviors, often under limited contextual conditions. We introduce D...
arXiv Computation and Language
Oct 1
Explore-on-Graph: Hybrid Embedding-LLM Reasoning for Knowledge Graph Question Answering under Incompleteness
arXiv:2609.39786v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly combined with knowledge graphs (KGs) to ground reasoning in structured evidence. However, most LLM-based...
arXiv AI
Oct 1
When a Kindergartener Solves Calculus: Measuring Capability Leakage in Role-Prompted Reasoning Models
arXiv:2609.39846v1 Announce Type: cross Abstract: We investigate the problem of role-capability leakage (RCL), in which a role-prompted reasoning model generates convincing in-role text while continu...
arXiv Computation and Language
Oct 1
Cognitive Enhancement: Rethinking the Necessity of Role-Playing for Large Language Models
arXiv:2609.39853v1 Announce Type: new Abstract: Role-playing prompting has become a popular yet simple technique for improving LLM reasoning and output quality. However, whether it consistently boost...