20 papers
How Creative Are Large Language Models in Generating Molecules?
Wen Tao, Yiwei Wang, Peng Zhou +6
Molecule generation requires satisfying multiple chemical and biological constraints while searching a large and structured chemical space. This makes it a non-binary problem, wher…
Visual CoT Makes VLMs Smarter but More Fragile
Chunxue Xu, Yiwei Wang, Yujun Cai +2
Chain-of-Thought (CoT) techniques have significantly enhanced reasoning in Vision-Language Models (VLMs). Extending this paradigm, Visual CoT integrates explicit visual edits, such…
How to Make Large Language Models Generate 100% Valid Molecules?
Wen Tao, Jing Tang, Alvin Chan +5
Molecule generation is key to drug discovery and materials science, enabling the design of novel compounds with specific properties. Large language models (LLMs) can learn to perfo…
DRS: Deep Question Reformulation With Structured Output
Zhecheng Li, Yiwei Wang, Bryan Hooi +3
Question answering represents a core capability of large language models (LLMs). However, when individuals encounter unfamiliar knowledge in texts, they often formulate questions t…
Vulnerability of LLMs to Vertically Aligned Text Manipulations
Zhecheng Li, Yiwei Wang, Bryan Hooi +4
Vertical text input is commonly encountered in various real-world applications, such as mathematical computations and word-based Sudoku puzzles. While current large language models…
Fact or Guesswork? Evaluating Large Language Models' Medical Knowledge with Structured One-Hop Judgments
Jiaxi Li, Yiwei Wang, Kai Zhang +5
Large language models (LLMs) have been widely adopted in various downstream task domains. However, their abilities to directly recall and apply factual medical knowledge remains un…