From the 1 of 7 linked papers with an AI index.
7 papers
Reliable isomorphic physics problem generation with large language models
Xian Wu, Lindim Ismaili
The paper describes an AI system that uses large language models to automatically create isomorphic physics problems, preserving the original problem structure while varying irrele…
From Guessing to Placeholding: A Cost-Theoretic Framework for Uncertainty-Aware Code Completion
Liang Zhu, Haolin Chen, Lidong Zhao +1
While Large Language Models (LLMs) have demonstrated exceptional proficiency in code completion, they typically adhere to a Hard Completion (HC) paradigm, compelling the generation…
Towards Real-world Human Behavior Simulation: Benchmarking Large Language Models on Long-horizon, Cross-scenario, Heterogeneous Behavior Traces
Jiawei Chen, Ruoxi Xu, Boxi Cao +11
The emergence of Large Language Models (LLMs) has illuminated the potential for a general-purpose user simulator. However, existing benchmarks remain constrained to isolated scenar…
Guaranteeing Knowledge Integration with Joint Decoding for Retrieval-Augmented Generation
Zhengyi Zhao, Shubo Zhang, Zezhong Wang +7
Retrieval-Augmented Generation (RAG) significantly enhances Large Language Models (LLMs) by providing access to external knowledge. However, current research primarily focuses on r…
ClawBench: Can AI Agents Complete Everyday Online Tasks?
Yuxuan Zhang, Yubo Wang, Yipeng Zhu +27
AI agents may be able to assist with emails and documents, but can they reliably complete everyday online workflows on real websites? Everyday online tasks offer a realistic yet un…
LaRS: Latent Reasoning Skills for Chain-of-Thought Reasoning
Zifan Xu, Haozhu Wang, Dmitriy Bespalov +3
Chain-of-thought (CoT) prompting is a popular in-context learning (ICL) approach for large language models (LLMs), especially when tackling complex reasoning tasks. Traditional ICL…