activity
20182024
most citedDelta Tuning: A Comprehensive Study of Parameter Efficient Methods for Pre-trained Language Models

21 citations · 67 across the 17 of their papers we have counts for

collaborators
Showing 2024Show all

5 papers · 1 filter

cs.LG2024★ 2 cited

AIGS: Generating Science from AI-Powered Automated Falsification

Zijun Liu, Kaiming Liu, Yiqi Zhu +5

Rapid development of artificial intelligence has drastically accelerated the development of scientific discovery. Trained with large-scale observation data, deep neural networks ex…

cs.AI2024★ 1 cited

ReAct Meets ActRe: When Language Agents Enjoy Training Data Autonomy

Zonghan Yang, Peng Li, Ming Yan +3

Language agents have demonstrated autonomous decision-making abilities by reasoning with foundation models. Recently, efforts have been made to train language agents for performanc…

cs.CV2024★ 1 cited

Scaffolding Coordinates to Promote Vision-Language Coordination in Large Multi-Modal Models

Xuanyu Lei, Zonghan Yang, Xinrui Chen +2

State-of-the-art Large Multi-Modal Models (LMMs) have demonstrated exceptional capabilities in vision-language tasks. Despite their advanced functionalities, the performances of LM…

cs.AI2024

Towards Unified Alignment Between Agents, Humans, and Environment

Zonghan Yang, An Liu, Zijun Liu +11

The rapid progress of foundation models has led to the prosperity of autonomous agents, which leverage the universal capabilities of foundation models to conduct reasoning, decisio…

cs.CL2024

PANDA: Preference Adaptation for Enhancing Domain-Specific Abilities of LLMs

An Liu, Zonghan Yang, Zhenhe Zhang +6

While Large language models (LLMs) have demonstrated considerable capabilities across various natural language tasks, they often fall short of the performance achieved by domain-sp…