2 citations · 3 across the 8 of their papers we have counts for
8 papers
MultEval: Supporting Collaborative Alignment for LLM-as-a-Judge Evaluation Criteria
Charles Chiang, Simret Gebreegziabher, Annalisa Szymanski +6
LLM-as-a-judge approaches have emerged as a scalable solution for evaluating model behaviors, yet they rely on evaluation criteria often created by a single individual, embedding t…
DiLLS: Interactive Diagnosis of LLM-based Multi-agent Systems via Layered Summary of Agent Behaviors
Rui Sheng, Yukun Yang, Chuhan Shi +4
Large language model (LLM)-based multi-agent systems have demonstrated impressive capabilities in handling complex tasks. However, the complexity of agentic behaviors makes these s…
The Behavioral Fabric of LLM-Powered GUI Agents: Human Values and Interaction Outcomes
Simret Araya Gebreegziabher, Yukun Yang, Charles Chiang +7
Large Language Model (LLM)-powered web GUI agents are increasingly automating everyday online tasks. Despite their popularity, little is known about how users' preferences and valu…
LMILAtt: A Deep Learning Model for Depression Detection from Social Media Users Enhanced by Multi-Instance Learning Based on Attention Mechanism
Yukun Yang
Depression is a major global public health challenge and its early identification is crucial. Social media data provides a new perspective for depression detection, but existing me…
L0: Reinforcement Learning to Become General Agents
Junjie Zhang, Jingyi Xi, Zhuoyang Song +7
Training large language models (LLMs) to act as autonomous agents for multi-turn, long-horizon tasks remains significant challenges in scalability and training efficiency. To addre…
Supporting Co-Adaptive Machine Teaching through Human Concept Learning and Cognitive Theories
Simret Araya Gebreegziabher, Yukun Yang, Elena L. Glassman +1
An important challenge in interactive machine learning, particularly in subjective or ambiguous domains, is fostering bi-directional alignment between humans and models. Users teac…
Coordinated Sparse Recovery of Label Noise
Yukun Yang, Naihao Wang, Haixin Yang +1
Label noise is a common issue in real-world datasets that inevitably impacts the generalization of models. This study focuses on robust classification tasks where the label noise i…
A theory for the sparsity emerged in the Forward Forward algorithm
Yukun Yang
This report explores the theory that explains the high sparsity phenomenon \citep{tosato2023emergent} observed in the forward-forward algorithm \citep{hinton2022forward}. The two t…