Papers by Junyi Ye
VEG: Verbal đťś–-greedy for Semantic Exploration in Multi-Turn RL Agents (2026.acl-industry)
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Yongchang Hao, Jie Hao, Yongsheng Mei, Ze Ye, Junyi Chai, Bin Guo, Benjamin Z. Yao, Chenlei Guo, Lili Mou
| Challenge: | Standard RL approaches suffer from reward sparsity and mode-seeking behavior . lack of diversity hinders exploration necessary for optimal learning . |
| Approach: | They propose a framework that leverages external feedback as a dynamic control variable to explicitly balance exploration and exploitation within the semantic space. |
| Outcome: | Experiments on Tau Bench and SearchQA show that the proposed framework outperforms standard RL baselines. |
Beyond End-to-End VLMs: Leveraging Intermediate Text Representations for Superior Flowchart Understanding (2025.naacl-long)
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| Challenge: | Flowcharts are typically presented as images, driving the trend of using vision-language models for end-to-end flowchart understanding. |
| Approach: | They propose a vision-language model (VLM) that generates textual representations from flowchart images and a textual Reasoner that performs question-answering based on the text representations. |
| Outcome: | Experiments on the FlowVQA and FlowLearn benchmarks demonstrate TextFlow’s state-of-the-art performance as well as its robustness. |