10 papers
Bridging Auxiliary Constraints to Resolve Instruction Following in Large Reasoning Models
Zhengyi Zhao, Shubo Zhang, Huimin Wang +7
Large Reasoning Models (LRMs) have demonstrated impressive capabilities in many tasks, yet they struggle with reliably following multiple instructions, either by failing to satisfy…
Beyond the Literal: Decomposing Pragmatic Intent in Multimodal Meme Understanding
Zhengyi Zhao, Shubo Zhang, Zezhong Wang +6
When asked what a meme or sarcastic post means, Large Vision Language Models (LVLMs) tend to describe what the image shows rather than what the author is trying to communicate. Sta…
Robust Tool Use via Fission-GRPO: Learning to Recover from Execution Errors
Zhiwei Zhang, Fei Zhao, Rui Wang +6
Large language models (LLMs) can call tools effectively, yet they remain brittle in multi-turn execution: after a tool-call error, smaller models often fall into repetitive invalid…
Guaranteeing Knowledge Integration with Joint Decoding for Retrieval-Augmented Generation
Zhengyi Zhao, Shubo Zhang, Zezhong Wang +7
Retrieval-Augmented Generation (RAG) significantly enhances Large Language Models (LLMs) by providing access to external knowledge. However, current research primarily focuses on r…
MemeReaCon: Probing Contextual Meme Understanding in Large Vision-Language Models
Zhengyi Zhao, Shubo Zhang, Yuxi Zhang +10
Memes have emerged as a popular form of multimodal online communication, where their interpretation heavily depends on the specific context in which they appear. Current approaches…
T: An Adaptive Test-Time Scaling Strategy for Contextual Question Answering
Zhengyi Zhao, Shubo Zhang, Zezhong Wang +7
Recent advances in Large Language Models (LLMs) have demonstrated remarkable performance in Contextual Question Answering (CQA). However, prior approaches typically employ elaborat…