7 citations · 8 across the 9 of their papers we have counts for
10 papers
Learning to GUIDE the Group: Self-Learning LLM Facilitation Across Multi-Party Tasks
Ziyi Liu, Tzu-Sheng Kuo, Jiale Liu +3
As large language models are increasingly adopted as multi-party communication facilitators, there is a growing demand for agents capable of balancing diverse group dynamics across…
LongVideoAgent: Multi-Agent Reasoning with Long Videos
Runtao Liu, Ziyi Liu, Jiaqi Tang +4
Recent advances in multimodal LLMs and systems that use tools for long-video QA point to the promise of reasoning over hour-long episodes. However, many methods still compress cont…
PersonaMem-v2: Towards Personalized Intelligence via Learning Implicit User Personas and Agentic Memory
Bowen Jiang, Yuan Yuan, Maohao Shen +13
Personalization is one of the next milestones in advancing AI capability and alignment. We introduce PersonaMem-v2, the state-of-the-art dataset for LLM personalization that simula…
LLM-Powered Text-Attributed Graph Anomaly Detection via Retrieval-Augmented Reasoning
Haoyan Xu, Ruizhi Qian, Zhengtao Yao +10
Anomaly detection on attributed graphs plays an essential role in applications such as fraud detection, intrusion monitoring, and misinformation analysis. However, text-attributed…
ProMediate: A Socio-cognitive framework for evaluating proactive agents in multi-party negotiation
Ziyi Liu, Bahar Sarrafzadeh, Pei Zhou +3
While Large Language Models (LLMs) are increasingly used in agentic frameworks to assist individual users, there is a growing need for agents that can proactively manage complex, m…
A State-Update Prompting Strategy for Efficient and Robust Multi-turn Dialogue
Ziyi Liu
Large Language Models (LLMs) struggle with information forgetting and inefficiency in long-horizon, multi-turn dialogues. To address this, we propose a training-free prompt enginee…
Causal Interventions on Causal Paths: Mapping GPT-2's Reasoning From Syntax to Semantics
Isabelle Lee, Joshua Lum, Ziyi Liu +1
While interpretability research has shed light on some internal algorithms utilized by transformer-based LLMs, reasoning in natural language, with its deep contextuality and ambigu…
InterIntent: Investigating Social Intelligence of LLMs via Intention Understanding in an Interactive Game Context
Ziyi Liu, Abhishek Anand, Pei Zhou +2
Large language models (LLMs) have demonstrated the potential to mimic human social intelligence. However, most studies focus on simplistic and static self-report or performance-bas…
Self-Contradictory Reasoning Evaluation and Detection
Ziyi Liu, Soumya Sanyal, Isabelle Lee +4
In a plethora of recent work, large language models (LLMs) demonstrated impressive reasoning ability, but many proposed downstream reasoning tasks only focus on final answers. Two…
Bootstrap Your Own Skills: Learning to Solve New Tasks with Large Language Model Guidance
Jesse Zhang, Jiahui Zhang, Karl Pertsch +5
We propose BOSS, an approach that automatically learns to solve new long-horizon, complex, and meaningful tasks by growing a learned skill library with minimal supervision. Prior w…