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Understand new AI research with readable explanations and links to the original papers.
From Score Matrices to Football-Aware Match-State Simulation: An Auditable LLM Harness for Exact-Score Reranking explores a hybrid architecture designed to i...
OctoLong: Mid-Training On Cross-Repository Code Contexts Enhances Long-Context Modeling introduces a pipeline designed to improve how language models handle...
WorldCycle is a reinforcement learning framework designed to improve long-horizon video world models by addressing the compounding errors that occur during a...
CoPlan is a human-AI interface designed to support care planning for aging-in-place.
ABSeeker is a framework designed to improve how long-horizon search agents are trained.
HiGram is a framework designed to improve how LLM agents manage long-term memory. By organizing information into a hierarchical graph rather than a flat stru...
When Outputs Disperse, Does Epistemic Revision Follow? A Black-Box Coupling Diagnostic for Machine Collectives investigates whether increasing the diversity...
ADMITBench is a reference framework designed to evaluate industrial Large Language Model (LLM) advisories by focusing on the admissibility of proposed action...
Foundation model agents can achieve stable cooperation in social dilemmas by using similarity inference, a departure from classical game theory predictions.
This paper provides the first practical implementation of the causal perception framework originally proposed by Álvarez and Ruggieri (2025).
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