3 citations · 3 across the 4 of their papers we have counts for
4 papers
Can LLM design high-quality experiments? A Comprehensive and Systematic Benchmark on Autonomous Experimental Design
Zejun Liu, Jian Wu, Ru Peng +4
AI for Research (AI4Research) leverages AI to automate and improve scientific workflows. While experimental design is a critical stage of the research process, prior work has focus…
Linear Reasoning vs. Proof by Cases: Obstacles for Large Language Models in FOL Problem Solving
Yuliang Ji, Fuchen Shen, Jian Wu +2
To comprehensively evaluate the mathematical reasoning capabilities of Large Language Models (LLMs), researchers have introduced abundant mathematical reasoning datasets. However,…
Rethinking Neural-based Matrix Inversion: Why can't, and Where can
Yuliang Ji, Jian Wu, Yuanzhe Xi
Deep neural networks have achieved substantial success across various scientific computing tasks. A pivotal challenge within this domain is the rapid and parallel approximation of…
GenDec: A robust generative Question-decomposition method for Multi-hop reasoning
Jian Wu, Linyi Yang, Yuliang Ji +3
Multi-hop QA (MHQA) involves step-by-step reasoning to answer complex questions and find multiple relevant supporting facts. However, Existing large language models'(LLMs) reasonin…