activity
20242026
most citedBioMamba: Domain-Adaptive Biomedical Language Models

2 citations · 2 across the 2 of their papers we have counts for

collaborators

5 papers

cs.CL20262 cited

BioMamba: Domain-Adaptive Biomedical Language Models

Ling Yue, Mingzhi Zhu, Sixue Xing +8

Background. Biomedical language models should improve performance on biomedical text while retaining general-language-modeling fluency. For Mamba-based models, this trade-off has n…

cs.CL2026

Compute Allocation in Evolutionary Search: From Depth-Breadth to Multi-Armed Bandits

Sixue Xing, Haoyu He, Kerui Wu +4

LLM-guided evolutionary search (Evolve systems) has reached state-of-the-art results on mathematical and combinatorial tasks, yet most existing systems report only the best of many…

cs.AI2026

ClinicalReTrial: Clinical Trial Redesign with Self-Evolving Agents

Sixue Xing, Kerui Wu, Xuanye Xia +3

Clinical trials constitute a critical yet exceptionally challenging and costly stage of drug development ($2.6B per drug), where protocols are encoded as complex natural language…

cs.CL2025

Exploring the Robustness of Language Models for Tabular Question Answering via Attention Analysis

Kushal Raj Bhandari, Sixue Xing, Soham Dan +1

Large Language Models (LLMs), already shown to ace various unstructured text comprehension tasks, have also remarkably been shown to tackle table (structured) comprehension tasks w…

cs.AI2024

PIANIST: Learning Partially Observable World Models with LLMs for Multi-Agent Decision Making

Jonathan Light, Sixue Xing, Yuanzhe Liu +7

Effective extraction of the world knowledge in LLMs for complex decision-making tasks remains a challenge. We propose a framework PIANIST for decomposing the world model into seven…