46 citations · 92 across the 13 of their papers we have counts for
4 papers · 1 filter
ORION: Teaching Language Models to Reason Efficiently in the Language of Thought
Kumar Tanmay, Kriti Aggarwal, Paul Pu Liang +1
Large Reasoning Models (LRMs) achieve strong performance in mathematics, code generation, and task planning, but their reliance on long chains of verbose "thinking" tokens leads to…
TRAJECT-Bench:A Trajectory-Aware Benchmark for Evaluating Agentic Tool Use
Pengfei He, Zhenwei Dai, Bing He +10
Large language model (LLM)-based agents increasingly rely on tool use to complete real-world tasks. While existing works evaluate the LLMs' tool use capability, they largely focus…
GraphGhost: Tracing Structures Behind Large Language Models
Xinnan Dai, Xianxuan Long, Chung-Hsiang Lo +4
Large Language Models (LLMs) exhibit strong reasoning capabilities on structured tasks, yet the internal mechanisms underlying such behaviors remain poorly understood. Existing int…
Retrieval-Augmented Generation with Graphs (GraphRAG)
Haoyu Han, Yu Wang, Harry Shomer +15
Retrieval-augmented generation (RAG) is a powerful technique that enhances downstream task execution by retrieving additional information, such as knowledge, skills, and tools from…