13 citations · 27 across the 9 of their papers we have counts for
10 papers
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…
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…
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…
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…
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…
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…
Pareto Domain Adaptation
Fangrui Lv, Jian Liang, Kaixiong Gong +5
Domain adaptation (DA) attempts to transfer the knowledge from a labeled source domain to an unlabeled target domain that follows different distribution from the source. To achieve…
Incentive Compatible Pareto Alignment for Multi-Source Large Graphs
Jian Liang, Fangrui Lv, Di Liu +5
In this paper, we focus on learning effective entity matching models over multi-source large-scale data. For real applications, we relax typical assumptions that data distributions…
Semantic Concentration for Domain Adaptation
Shuang Li, Mixue Xie, Fangrui Lv +4
Domain adaptation (DA) paves the way for label annotation and dataset bias issues by the knowledge transfer from a label-rich source domain to a related but unlabeled target domain…
Bi-Classifier Determinacy Maximization for Unsupervised Domain Adaptation
Shuang Li, Fangrui Lv, Binhui Xie +3
Unsupervised domain adaptation challenges the problem of transferring knowledge from a well-labelled source domain to an unlabelled target domain. Recently,adversarial learning wit…