12 citations · 13 across the 6 of their papers we have counts for
6 papers
Difference Feedback: Generating Multimodal Process-Level Supervision for VLM Reinforcement Learning
Feiding, Yongkang Zhang, Yuhao Liao +10
Vision--language models (VLMs) are increasingly aligned via Group Relative Policy Optimization (GRPO)-style training. However, relying solely on terminal outcome rewards yields spa…
SimRPD: Optimizing Recruitment Proactive Dialogue Agents through Simulator-Based Data Evaluation and Selection
Zhiyong Cao, Dunqiang Liu, Qi Dai +9
Task-oriented proactive dialogue agents play a pivotal role in recruitment, particularly for steering conversations towards specific business outcomes, such as acquiring social-med…
AndesVL Technical Report: An Efficient Mobile-side Multimodal Large Language Model
Zhiwei Jin, Xiaohui Song, Nan Wang +36
In recent years, while cloud-based MLLMs such as QwenVL, InternVL, GPT-4o, Gemini, and Claude Sonnet have demonstrated outstanding performance with enormous model sizes reaching hu…
GenX: Mastering Code and Test Generation with Execution Feedback
Nan Wang, Yafei Liu, Chen Chen +1
Recent advancements in language modeling have enabled the translation of natural language into code, and the use of execution feedback to improve code generation. However, these me…
InsCL: A Data-efficient Continual Learning Paradigm for Fine-tuning Large Language Models with Instructions
Yifan Wang, Yafei Liu, Chufan Shi +4
Instruction tuning effectively optimizes Large Language Models (LLMs) for downstream tasks. Due to the changing environment in real-life applications, LLMs necessitate continual ta…
Interactive Interior Design Recommendation via Coarse-to-fine Multimodal Reinforcement Learning
He Zhang, Ying Sun, Weiyu Guo +4
Personalized interior decoration design often incurs high labor costs. Recent efforts in developing intelligent interior design systems have focused on generating textual requireme…