Guiyang Hou

Orcid: 0009-0009-9163-0633

According to our database1, Guiyang Hou authored at least 17 papers between 2023 and 2025.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

On csauthors.net:

Bibliography

2025
Cooper: Co-Optimizing Policy and Reward Models in Reinforcement Learning for Large Language Models.
CoRR, August, 2025

SVGenius: Benchmarking LLMs in SVG Understanding, Editing and Generation.
CoRR, June, 2025

TimeHC-RL: Temporal-aware Hierarchical Cognitive Reinforcement Learning for Enhancing LLMs' Social Intelligence.
CoRR, May, 2025

ViewSpatial-Bench: Evaluating Multi-perspective Spatial Localization in Vision-Language Models.
CoRR, May, 2025

Mind the Gap: Bridging Thought Leap for Improved Chain-of-Thought Tuning.
CoRR, May, 2025

A Survey on (M)LLM-Based GUI Agents.
CoRR, April, 2025

Embodied-Reasoner: Synergizing Visual Search, Reasoning, and Action for Embodied Interactive Tasks.
CoRR, March, 2025

Think Twice, Click Once: Enhancing GUI Grounding via Fast and Slow Systems.
CoRR, March, 2025

Scaling LLMs' Social Reasoning: Sprinkle Cognitive "Aha Moment" into Fundamental Long-thought Logical Capabilities.
Proceedings of the Findings of the Association for Computational Linguistics, 2025

2024
Specialized Mathematical Solving by a Step-By-Step Expression Chain Generation.
IEEE ACM Trans. Audio Speech Lang. Process., 2024

GaVaMoE: Gaussian-Variational Gated Mixture of Experts for Explainable Recommendation.
CoRR, 2024

Entering Real Social World! Benchmarking the Theory of Mind and Socialization Capabilities of LLMs from a First-person Perspective.
CoRR, 2024

Multimodal Self-Instruct: Synthetic Abstract Image and Visual Reasoning Instruction Using Language Model.
Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

Agent-Pro: Learning to Evolve via Policy-Level Reflection and Optimization.
Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024

TimeToM: Temporal Space is the Key to Unlocking the Door of Large Language Models' Theory-of-Mind.
Proceedings of the Findings of the Association for Computational Linguistics, 2024

Progressive Tuning: Towards Generic Sentiment Abilities for Large Language Models.
Proceedings of the Findings of the Association for Computational Linguistics, 2024

2023
Enhancing Emotion Recognition in Conversation via Multi-view Feature Alignment and Memorization.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023


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