1.2k citations · 1.3k across the 14 of their papers we have counts for
14 papers
Agent Lumos: Unified and Modular Training for Open-Source Language Agents
Da Yin, Faeze Brahman, Abhilasha Ravichander +4
Closed-source agents suffer from several issues such as a lack of affordability, transparency, and reproducibility, particularly on complex interactive tasks. This motivates the de…
The Magic of IF: Investigating Causal Reasoning Abilities in Large Language Models of Code
Xiao Liu, Da Yin, Chen Zhang +2
Causal reasoning, the ability to identify cause-and-effect relationship, is crucial in human thinking. Although large language models (LLMs) succeed in many NLP tasks, it is still…
Dynosaur: A Dynamic Growth Paradigm for Instruction-Tuning Data Curation
Da Yin, Xiao Liu, Fan Yin +4
Instruction tuning has emerged to enhance the capabilities of large language models (LLMs) to comprehend instructions and generate appropriate responses. Existing methods either ma…
KPEval: Towards Fine-Grained Semantic-Based Keyphrase Evaluation
Di Wu, Da Yin, Kai-Wei Chang
Despite the significant advancements in keyphrase extraction and keyphrase generation methods, the predominant approach for evaluation mainly relies on exact matching with human re…
GIVL: Improving Geographical Inclusivity of Vision-Language Models with Pre-Training Methods
Da Yin, Feng Gao, Govind Thattai +2
A key goal for the advancement of AI is to develop technologies that serve the needs not just of one group but of all communities regardless of their geographical region. In fact,…
How well can Text-to-Image Generative Models understand Ethical Natural Language Interventions?
Hritik Bansal, Da Yin, Masoud Monajatipoor +1
Text-to-image generative models have achieved unprecedented success in generating high-quality images based on natural language descriptions. However, it is shown that these models…