1 citations · 1 across the 9 of their papers we have counts for
12 papers
Of Errors and Echoes: Responsibility-Aware Credit Assignment for Tool-Use Agents
Xingjian Diao, Tianyu Yang, Wenjun Huang +8
Reinforcement learning improves tool-use agents, yet fine-grained credit assignment remains challenging even with step-level feedback. An observed error may be inherited from an ea…
Addressing Overthinking in Large Vision-Language Models via Gated Perception-Reasoning Optimization
Xingjian Diao, Zheyuan Liu, Chunhui Zhang +6
Large Vision-Language Models (LVLMs) have exhibited strong reasoning capabilities through chain-of-thought mechanisms that generate step-by-step rationales. However, such slow-thin…
Learning Sparsity for Effective and Efficient Music Performance Question Answering
Xingjian Diao, Tianzhen Yang, Chunhui Zhang +3
Music performances, characterized by dense and continuous audio as well as seamless audio-visual integration, present unique challenges for multimodal scene understanding and reaso…
Growing Through Experience: Scaling Episodic Grounding in Language Models
Chunhui Zhang, Sirui, Wang +3
Language models (LMs) require robust episodic grounding-the capacity to learn from and apply past experiences-to excel at physical planning tasks. Current episodic grounding approa…
SoundMind: RL-Incentivized Logic Reasoning for Audio-Language Models
Xingjian Diao, Chunhui Zhang, Keyi Kong +6
While large language models have demonstrated impressive reasoning abilities, their extension to the audio modality, particularly within large audio-language models (LALMs), remain…
What Makes LLMs Effective Sequential Recommenders? A Study on Preference Intensity and Temporal Context
Zhongyu Ouyang, Qianlong Wen, Chunhui Zhang +2
What enables large language models (LLMs) to effectively model user preferences in sequential recommendation? Our investigation reveals that existing preference-alignment approache…
Overcoming Multi-step Complexity in Multimodal Theory-of-Mind Reasoning: A Scalable Bayesian Planner
Chunhui Zhang, Zhongyu Ouyang, Kwonjoon Lee +4
Theory-of-Mind (ToM) enables humans to infer mental states-such as beliefs, desires, and intentions-forming the foundation of social cognition. However, existing computational ToM…
Music Audio-Visual Question Answering Requires Specialized Multimodal Designs
Wenhao You, Xingjian Diao, Wenjun Huang +9
While recent Multimodal Large Language Models exhibit impressive capabilities for general multimodal tasks, specialized domains like music necessitate tailored approaches. Music Au…
Pretrained Image-Text Models are Secretly Video Captioners
Chunhui Zhang, Yiren Jian, Zhongyu Ouyang +1
Developing video captioning models is computationally expensive. The dynamic nature of video also complicates the design of multimodal models that can effectively caption these seq…
Learning Musical Representations for Music Performance Question Answering
Xingjian Diao, Chunhui Zhang, Tingxuan Wu +4
Music performances are representative scenarios for audio-visual modeling. Unlike common scenarios with sparse audio, music performances continuously involve dense audio signals th…
Is It Navajo? Accurate Language Detection in Endangered Athabaskan Languages
Ivory Yang, Weicheng Ma, Chunhui Zhang +1
Endangered languages, such as Navajo - the most widely spoken Native American language - are significantly underrepresented in contemporary language technologies, exacerbating the…
Temporal Working Memory: Query-Guided Segment Refinement for Enhanced Multimodal Understanding
Xingjian Diao, Chunhui Zhang, Weiyi Wu +5
Multimodal foundation models (MFMs) have demonstrated significant success in tasks such as visual captioning, question answering, and image-text retrieval. However, these models fa…