Papers by Beibei Yu
A Survey of Large Language Models in Psychotherapy: Current Landscape and Future Directions (2025.findings-acl)
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Hongbin Na, Yining Hua, Zimu Wang, Tao Shen, Beibei Yu, Lilin Wang, Wei Wang, John Torous, Ling Chen
| Challenge: | Large language models (LLMs) can handle extensive context and multi-turn reasoning. |
| Approach: | They propose a taxonomy dividing psychotherapy into stages of assessment, diagnosis, and treatment to examine LLM advancements and challenges. |
| Outcome: | The proposed taxonomy reveals imbalances in current research, such as a focus on common disorders, linguistic biases, fragmented methods, and limited theoretical integration. |
Intent-Driven Semantic ID Generation for Grounded Conversational News Recommendation (2026.acl-industry)
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| Challenge: | a new approach to news recommendation grounds each suggestion in a rapidly evolving article corpus while addressing implicit user intents that lack explicit retrievable keywords. |
| Approach: | They propose an intent-driven Semantic ID generation paradigm to address these challenges . they map diverse intents to hierarchical SID prefixes and then fuzzy-match them to current news pool . |
| Outcome: | The proposed model achieves 0% hallucination and 12.4% L1 match on a mainstream Chinese news platform. |
STA-CoT: Structured Target-Centric Agentic Chain-of-Thought for Consistent Multi-Image Geological Reasoning (2025.findings-emnlp)
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| Challenge: | Reliable multi-image geological reasoning is essential for automating expert tasks in remote-sensing mineral exploration. |
| Approach: | They propose a framework that orchestrates planning, execution, and verification agents to decompose, ground, and iteratively refine reasoning steps over geological and hyperspectral image sets. |
| Outcome: | The proposed framework decomposes, ground, and iteratively refines reasoning steps over geological and hyperspectral image sets. |