1 citations · 1 across the 6 of their papers we have counts for
10 papers
Minimal Complexes of Rational Tangles via the Fukaya Category
Jonathan A. Higgins
We compute minimal complexes for oriented rational tangles, denoted , in terms of the topological Fukaya category of the -punctured disk…
MOF-VERIFY: A Failure-Aware Agentic Harness for MOF Hypothesis Verification
Donghyun Lee, Taehoon Lee, Geonhee Ahn +10
Large language models are increasingly used as reasoning components in AI-driven materials Co-Scientists, yet the reliability of the resulting verification pipeline remains unclear…
Recursive Harness Self-Improvement
Hyunin Lee, Jinglue Xu, Jeffrey Seely +3
Under model--harness co-evolution, harnesses are not merely inference-time scaffolds but data-generating components whose execution traces can shape future foundation models. This…
AgentBeats: Agentifying Agent Assessment for Openness, Standardization, and Reproducibility
Xiaoyuan Liu, Jianhong Tu, Yuqi Chen +26
Agent systems are advancing quickly across domains, but their evaluation remains fragmented. Most benchmarks rely on fixed, LLM-centric harnesses that require heavy integration, cr…
optimize_anything: A Universal API for Optimizing any Text Parameter
Lakshya A Agrawal, Donghyun Lee, Shangyin Tan +11
Can a single LLM-based optimization system match specialized tools across fundamentally different domains? We show that when optimization problems are formulated as improving a tex…
MIND: AI Co-Scientist for Material Research
Geonhee Ahn, Donghyun Lee, Hayoung Doo +3
Large language models (LLMs) have enabled agentic AI systems for scientific discovery, but most approaches remain limited to textbased reasoning without automated experimental veri…
AMRG: Extend Vision Language Models for Automatic Mammography Report Generation
Nak-Jun Sung, Donghyun Lee, Bo Hwa Choi +1
Mammography report generation is a critical yet underexplored task in medical AI, characterized by challenges such as multiview image reasoning, high-resolution visual cues, and un…
Prompt Infection: LLM-to-LLM Prompt Injection within Multi-Agent Systems
Donghyun Lee, Mo Tiwari
As Large Language Models (LLMs) grow increasingly powerful, multi-agent systems are becoming more prevalent in modern AI applications. Most safety research, however, has focused on…
CATS: Contextually-Aware Thresholding for Sparsity in Large Language Models
Donghyun Lee, Je-Yong Lee, Genghan Zhang +2
Large Language Models (LLMs) have dramatically advanced AI applications, yet their deployment remains challenging due to their immense inference costs. Recent studies ameliorate th…
BanditPAM++: Faster -medoids Clustering
Mo Tiwari, Ryan Kang, Donghyun Lee +4
Clustering is a fundamental task in data science with wide-ranging applications. In -medoids clustering, cluster centers must be actual datapoints and arbitrary distance metrics…