activity
20242026
collaborators

7 papers

cs.CL2026

When Humans Leave Context Unsaid: Implicit Context as a Risk for Large Language Models

Bocheng Chen, Han Zi, Yuda Chen +6

Human language is grounded in pragmatics, necessitating implicit (extralinguistic) context to interpret language, e.g., world knowledge and social norms. However, such context is o…

cs.CL2026

Can Large Language Models Handle Discourse Particles? A Case Study of Colloquial Malay

Mariah Al Giptiah Binte Yusoff, Jakin Tan, Bocheng Chen +2

Discourse particles, such as well and kind of, are crucial components that enable LLMs to "speak" more like humans. They are used to convey emotions, intentions, and interpersonal…

cs.AI2026

Deactivating Refusal Triggers: Understanding and Mitigating Overrefusal in Safety Alignment

Zhiyu Xue, Zimo Qi, Guangliang Liu +2

Safety alignment aims to ensure that large language models (LLMs) refuse harmful requests by post-training on harmful queries paired with refusal answers. Although safety alignment…

cs.CL2026

Learning to Diagnose and Correct Moral Errors: Beyond Shallow Heuristics in Moral Alignment

Bocheng Chen, Xi Chen, Han Zi +5

Existing approaches to moral value alignment are primarily set out to align LLMs' generation with the distributions of morally appropriate language, which has seen good progress. H…

cs.CL2025

From Training to Generalization: Improving Moral Reasoning Through Pragmatic Inference

Guangliang Liu, Xi Chen, Bocheng Chen +3

Although moral reasoning has emerged as a promising research direction for large language models (LLMs), a persistent generalization challenge remains: LLMs often achieve strong pe…

cs.CL2025

Diagnosing the Performance Trade-off in Moral Alignment: A Case Study on Gender Stereotypes

Guangliang Liu, Bocheng Chen, Han Zi +2

Moral alignment has emerged as a widely adopted approach for regulating the behavior of pretrained language models (PLMs), typically through fine-tuning on curated datasets. Gender…

cs.CR2024

No Free Lunch for Defending Against Prefilling Attack by In-Context Learning

Zhiyu Xue, Guangliang Liu, Bocheng Chen +2

The security of Large Language Models (LLMs) has become an important research topic since the emergence of ChatGPT. Though there have been various effective methods to defend again…