7 citations · 12 across the 7 of their papers we have counts for
7 papers
Environment Scaling for Interactive Agentic Experience Collection: A Survey
Yuchen Huang, Sijia Li, Minghao Liu +5
LLM-based agents can autonomously accomplish complex tasks across various domains. However, to further cultivate capabilities such as adaptive behavior and long-term decision-makin…
PERSONA: A Reproducible Testbed for Pluralistic Alignment
Louis Castricato, Nathan Lile, Rafael Rafailov +2
The rapid advancement of language models (LMs) necessitates robust alignment with diverse user values. However, current preference optimization approaches often fail to capture the…
From Pixels to Insights: A Survey on Automatic Chart Understanding in the Era of Large Foundation Models
Kung-Hsiang Huang, Hou Pong Chan, Yi R. Fung +5
Data visualization in the form of charts plays a pivotal role in data analysis, offering critical insights and aiding in informed decision-making. Automatic chart understanding has…
Can LLMs Produce Faithful Explanations For Fact-checking? Towards Faithful Explainable Fact-Checking via Multi-Agent Debate
Kyungha Kim, Sangyun Lee, Kung-Hsiang Huang +3
Fact-checking research has extensively explored verification but less so the generation of natural-language explanations, crucial for user trust. While Large Language Models (LLMs)…
Persona-DB: Efficient Large Language Model Personalization for Response Prediction with Collaborative Data Refinement
Chenkai Sun, Ke Yang, Revanth Gangi Reddy +5
The increasing demand for personalized interactions with large language models (LLMs) calls for methodologies capable of accurately and efficiently identifying user opinions and pr…
Do LVLMs Understand Charts? Analyzing and Correcting Factual Errors in Chart Captioning
Kung-Hsiang Huang, Mingyang Zhou, Hou Pong Chan +5
Recent advancements in large vision-language models (LVLMs) have led to significant progress in generating natural language descriptions for visual content and thus enhancing vario…
Decoding the Silent Majority: Inducing Belief Augmented Social Graph with Large Language Model for Response Forecasting
Chenkai Sun, Jinning Li, Yi R. Fung +4
Automatic response forecasting for news media plays a crucial role in enabling content producers to efficiently predict the impact of news releases and prevent unexpected negative…