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Understand new AI research with readable explanations and links to the original papers.
Exact Regular-Constrained Variable-Order Markov Generation via Sparse Context-State Belief Propagation This paper addresses a fundamental challenge in sequen...
Learning CLI Agents with Structured Action Credit under Selective Observation This paper addresses the challenge of training AI agents to operate effectively...
TraceFix: Repairing Agent Coordination Protocols with TLA+ Counterexamples TraceFix is a new verification-first pipeline designed to solve the coordination f...
MPD$^2$-Router: Mask-aware Multi-expert Prior-regularized Dual-head Deferral Router in Glaucoma Screening and Diagnosis This paper introduces a new framework...
AgentEscapeBench is a new diagnostic benchmark designed to test how well AI agents can perform complex, multi-step reasoning when using external tools.
Mind the Gap? A Distributional Comparison of Real and Synthetic Priors for Tabular Foundation Models investigates how different types of data used to train T...
SkillOS is a research framework designed to help AI agents evolve by learning how to curate their own "skills." While many current AI agents solve tasks in i...
Measuring Black-Box Confidence via Reasoning Trajectories: Geometry, Coverage, and Verbalization This research addresses a critical challenge in AI: how to d...
SpatialEpiBench: Benchmarking Spatial Information and Epidemic Priors in Forecasting Epidemic forecasting is essential for public health, yet it remains a di...
SCRuB: Social Concept Reasoning under Rubric-Based Evaluation introduces a new way to measure how well Large Language Models (LLMs) handle "social concept re...
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