3 papers
cs.AI2025
Algorithmic Thinking Theory
MohammadHossein Bateni, Vincent Cohen-Addad, Yuzhou Gu +3
Large language models (LLMs) have proven to be highly effective for solving complex reasoning tasks. Surprisingly, their capabilities can often be improved by iterating on previous…
cs.LG2025
SYNAPSE-G: Bridging Large Language Models and Graph Learning for Rare Event Classification
Sasan Tavakkol, Lin Chen, Max Springer +4
Scarcity of labeled data, especially for rare events, hinders training effective machine learning models. This paper proposes SYNAPSE-G (Synthetic Augmentation for Positive Samplin…
cs.CL2024
Re-Invoke: Tool Invocation Rewriting for Zero-Shot Tool Retrieval
Yanfei Chen, Jinsung Yoon, Devendra Singh Sachan +5
Recent advances in large language models (LLMs) have enabled autonomous agents with complex reasoning and task-fulfillment capabilities using a wide range of tools. However, effect…