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Posts by Collection
portfolio
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publications
iSMOD: an integrative browser for image-based single-cell multi-omics data
Published in Nucleic Acids Research, 2023
This paper presents iSMOD, which is the first integrative browser for collecting and analyzing FISH and nucleus proteomics data. By integrating multi-omics studies from 20,000+ published papers, it provides powerful tools for exploring cellular mechanisms and advancing biological research through comprehensive data visualization and analysis.
STRUX: An LLM for Decision-Making with Structured Explanations
Published in NAACL, 2025
This paper presents STRUX, which is a novel LLM framework that enhances decision-making through structured explanations. By distilling complex information into key facts and employing self-reflection steps, it categorizes and prioritizes factors affecting decisions. We demonstrate its effectiveness in stock investment decisions based on earnings call transcripts, making LLM decision-making more transparent and practical.
DeFine: Enhancing LLM Decision-Making with Factor Profiles and Analogical Reasoning
Published in ACL Findings, 2025
This paper presents DeFine, a novel approach that bolsters LLM-based decision-making through factor profiles and analogical reasoning. By systematically identifying and comparing key factors across contexts, DeFine promotes deeper context comprehension and more robust inferences. Our experiments on finance-related reasoning tasks demonstrate its ability to deliver both higher accuracy and enhanced interpretability, with broader applications to various decision-making scenarios.
Communication to Completion: Modeling Collaborative Workflows with Intelligent Multi-Agent Communication
Published in Under Review, 2025
In this work, we introduce Communication to Completion (C2C), a scalable multi-agent framework that enhances task oriented collaboration through structured communication. C2C features the Alignment Factor (AF), a novel metric quantifying task understanding, and a Sequential Action Framework that enables cost aware communication decisions. Evaluated on realistic coding workflows across varying team sizes and complexity tiers, C2C reduces task completion time by 40%, establishing both theoretical foundations and practical utilities for communication efficient multi-agent systems.
talks
Talk 1 on Relevant Topic in Your Field
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Conference Proceeding talk 3 on Relevant Topic in Your Field
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teaching
Teaching experience 1
Undergraduate course, University 1, Department, 2014
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Teaching experience 2
Workshop, University 1, Department, 2015
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