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Understand new AI research with readable explanations and links to the original papers.
VAKRA (eValuating API and Knowledge Retrieval Agents) is a benchmark designed to measure how well AI agents perform multi-step reasoning when they must inter...
FedCGR is a federated learning framework designed to improve cross-domain recommendation (CDR) by treating it as a generative task.
XCoT-VLA is a framework designed to improve autonomous driving by replacing verbose, natural-language reasoning with compact, executable tokens.
sLTN: Structural Logic Tensor Networks introduces a neurosymbolic framework that extends Logic Tensor Networks (LTN) to explicitly handle structured data.
This paper presents a case study on using AI to conduct long-horizon mathematical research, specifically focusing on tightening the bounds of the Grothendiec...
ThinkRetrieve is a framework designed to improve the performance of Large Reasoning Models (LRMs) by injecting relevant, solved examples into their reasoning...
RTSKG: Building a Rail Transit Station Knowledge Graph Dataset introduces a structured dataset designed to help researchers analyze urban rail transit system...
Agentic coding repositories often rely on README files like CLAUDE.md to guide AI agents. This paper, "Why Does CLAUDE.md Keep Growing?
V-FiLLM is a framework designed to evaluate how well Large Language Models (LLMs) perform financial reasoning over structured data.
IO Factory is a research framework designed to simulate AI-driven influence campaigns as traceable, multi-stage processes.
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