Papers by Tianyang Zhao
On the Analysis and Distillation of Emergent Outlier Properties in Pre-trained Language Models (2025.naacl-long)
Copied to clipboard
| Challenge: | Existing studies show that a small subset of dimensions within language Transformers’ representation spaces emerge as "outliers" during pretraining. |
| Approach: | They propose a method that prioritizes critical outlier dimensions in distillation using a weighted MSE loss. |
| Outcome: | The proposed method outperforms state-of-the-art distillation methods and generalizes well across Encoder-only BERT, Decoder-only GPT-2, and Encodeer-Decoder T5 architectures. |
Towards Enhanced Immersion and Agency for LLM-based Interactive Drama (2025.acl-long)
Copied to clipboard
| Challenge: | Existing studies have focused on the role of immersion and agency in interactive drama. |
| Approach: | They propose a playwriting-guided generation method that helps LLMs craft dramatic stories with substantially improved structures and narrative quality. |
| Outcome: | The proposed method improves storytelling quality and immersion and agency, while allowing agents to refine their reactions to align with the player’s intentions. |
Enhancing Dialogue-based Relation Extraction by Speaker and Trigger Words Prediction (2021.findings-acl)
Copied to clipboard
| Challenge: | Existing methods for identifying relations from dialogues do not fully consider the particularity of dialogues, making them difficult to understand the semantics between conversational arguments. |
| Approach: | They propose two tasks to enhance the extraction of dialogue-based relations . speaker prediction captures the characteristics of speakerrelated entities . the trigger words prediction provides supportive contexts for relations between arguments . |
| Outcome: | The proposed tasks improve the extraction of dialogue-based relations . speaker prediction captures the characteristics of speakerrelated entities . the trigger words prediction provides supportive contexts for relations between arguments . |
Not All Directions Matter: Towards Structured and Task-Aware Low-Rank Model Adaptation (2026.acl-long)
Copied to clipboard
Xi Xiao, Chenrui Ma, Yunbei Zhang, Chen Liu, Zhuxuanzi Wang, Yanshu Li, Lin Zhao, Guosheng Hu, Tianyang Wang, Hao Xu
| Challenge: | Low-Rank Adaptation (LoRA) is a key parameter-efficient fine-tuning method . however, its effectiveness is hampered by semantic drift and structural incoherence . |
| Approach: | They propose a low-rank Adaptation framework that tackles semantic drift and structural incoherence by pruning task-irrelevant directions. |
| Outcome: | Experiments on large language models, vision models, and vision models show that the proposed framework outperforms LoRA and advanced dynamic rank allocation and sparsity-based methods. |
Open-Theatre: An Open-Source Toolkit for LLM-based Interactive Drama (2025.emnlp-demos)
Copied to clipboard
| Challenge: | Existing tools for creating, modifying, and experimenting with interactive dramas are limited. |
| Approach: | They propose an open-source toolkit for creating configurable LLM-based interactive drama. |
| Outcome: | The proposed toolkit enhances narrative coherence and realistic behavior in interactions with agents. |