activity
20202026
most citedCausality Inspired Representation Learning for Domain Generalization

13 citations · 27 across the 9 of their papers we have counts for

collaborators

10 papers

cs.MA2026

TACO: Tool-Augmented Credit Optimization for Agentic Tool Use

Mingkuan Feng, Jinyang Wu, Hao Gu +5

Agentic multimodal models perform diverse operations on an image via code and reason over the returned view, an effective paradigm for fine-grained visual question answering. Howev…

cs.CL2026

Deliberate Evolution: Agentic Reasoning for Sample-Efficient Symbolic Regression with LLMs

Xinyu Pang, Zhanke Zhou, Xuan Li +5

Symbolic regression (SR) discovers compact mathematical expressions from data, yet recent LLM-based evolutionary methods remain sample-inefficient because they rely mainly on scala…

cs.CV2026

MetaphorVU: Towards Metaphorical Video Understanding

Zhuoqun Li, Boxi Cao, Guiping Jiang +13

Metaphorical videos are prevalent across various real-world scenarios to convey complex ideas, and understanding them typically requires high-order cognitive capabilities. The lack…

cs.CV2023★ 1 cited

Towards Unified and Effective Domain Generalization

Yiyuan Zhang, Kaixiong Gong, Xiaohan Ding +4

We propose , a novel and fied framework for omain eneralization that is capable of significantly enhancing the out-of-distribu…

cs.CV2023

Improving Generalization with Domain Convex Game

Fangrui Lv, Jian Liang, Shuang Li +2

Domain generalization (DG) tends to alleviate the poor generalization capability of deep neural networks by learning model with multiple source domains. A classical solution to DG…

cs.LG2022★ 13 cited

Causality Inspired Representation Learning for Domain Generalization

Fangrui Lv, Jian Liang, Shuang Li +4

Domain generalization (DG) is essentially an out-of-distribution problem, aiming to generalize the knowledge learned from multiple source domains to an unseen target domain. The ma…