Papers by Dingyu Yang
EoT: Evolution of Thoughts for Complex Reasoning Tasks (2025.findings-emnlp)
Copied to clipboard
| Challenge: | Existing studies focus on ensuring behavior fidelity, factuality or reliability in generated reasoning processes, but they neglect the simultaneous optimization of all three aspects for each thought. |
| Approach: | They propose a thought assessment method that is sensitive to knowledge and LLM behaviors . they use three scorers to evaluate each thought by considering domain context, semantic alignment, and behavior impact. |
| Outcome: | The proposed framework outperforms advanced approaches in knowledge-based complex tasks. |
EmoRes: Toward Adaptive Psychological Support via User-Agnostic Benchmark and Topic-Mining Agent (2026.findings-acl)
Copied to clipboard
Zhengwei Zou, Xuanming Jiang, Baoyi An, Dingyu Nie, Zhengxing Fang, Qingyu Liu, Xueming Qian, Guoshuai Zhao, Zhongyu Yang
| Challenge: | Large language models generate fragmented and emotionally inconsistent dialogues lacking the therapeutic structure necessary for reliable assessment. |
| Approach: | They propose a framework that boosts psychological reasoning via a Topic-Mining Emotional Agent and a multi-perspective Self-Reflection Agent. |
| Outcome: | The proposed framework improves topic continuity, emotional coherence, and clinical interpretability over baselines and validated by ablation studies and human evaluations. |
VecInfer: Efficient LLM Inference with Low-Bit KV Cache via Outlier-Suppressed Vector Quantization (2026.acl-long)
Copied to clipboard
| Challenge: | Existing quantization methods for large language models suffer performance degradation at ultra-low bit-widths due to key cache outliers. |
| Approach: | They propose a vector quantization method that suppresses outliers in the key cache and reduces memory access overhead. |
| Outcome: | The proposed method outperforms baseline quantization methods across long-context understanding and mathematical reasoning tasks while minimizing memory access overhead. |