1 citations · 1 across the 8 of their papers we have counts for
9 papers
OmniFysics-Captioner Technical Report: Grounding Omni-Modal Understanding in the Physical World for Better Captioning
Kaixiang Qiu, Minghao Han, Keliang Liu +7
Building omni-modal models with physical intelligence requires fine-grained supervision that captures physical evidence such as contact, support, deformation, and state transitions…
TeachPro: Multi-Label Qualitative Teaching Evaluation via Cross-View Graph Synergy and Semantic Anchored Evidence Encoding
Xiangqian Wang, Yifan Jia, Yang Xiang +3
Standardized Student Evaluation of Teaching often suffer from low reliability, restricted response options, and response distortion. Existing machine learning methods that mine ope…
Resolving Evidence Sparsity: Agentic Context Engineering for Long-Document Understanding
Keliang Liu, Zizhi Chen, Mingcheng Li +3
Document understanding is a long standing practical task. Vision Language Models (VLMs) have gradually become a primary approach in this domain, demonstrating effective performance…
Improving Multimodal Sentiment Analysis via Modality Optimization and Dynamic Primary Modality Selection
Dingkang Yang, Mingcheng Li, Xuecheng Wu +5
Multimodal Sentiment Analysis (MSA) aims to predict sentiment from language, acoustic, and visual data in videos. However, imbalanced unimodal performance often leads to suboptimal…
Reinforcement Learning Meets Large Language Models: A Survey of Advancements and Applications Across the LLM Lifecycle
Keliang Liu, Dingkang Yang, Ziyun Qian +7
In recent years, training methods centered on Reinforcement Learning (RL) have markedly enhanced the reasoning and alignment performance of Large Language Models (LLMs), particular…
Generative Sequential Notification Optimization via Multi-Objective Decision Transformers
Borja Ocejo, Ruofan Wang, Ke Liu +7
Notifications are an important communication channel for delivering timely and relevant information. Optimizing their delivery involves addressing complex sequential decision-makin…
GOSU: Retrieval-Augmented Generation with Global-Level Optimized Semantic Unit-Centric Framework
Xuecheng Zou, Ke Liu, Bingbing Wang +3
Building upon the standard graph-based Retrieval-Augmented Generation (RAG), the introduction of heterogeneous graphs and hypergraphs aims to enrich retrieval and generation by lev…
Adaptive Reinforcement for Open-ended Medical Reasoning via Semantic-Guided Reward Collapse Mitigation
Yizhou Liu, Dingkang Yang, Zizhi Chen +5
Reinforcement learning (RL) with rule-based reward functions has recently shown great promise in enhancing the reasoning depth and generalization ability of vision-language models…
SheetMind: Actions Set Accuracy, Agents Set the Failure Mode
Xi Cheng, Ruiyan Zhu, Yanming Kang +11
Spreadsheet agents are converging on elaborate multi-agent designs, yet it is unclear how much of their performance comes from the agents rather than from the action interface they…