5 papers · 1 filter
Pragmatic Attack Surface: Vulnerabilities of Implicit Context in Large Language Models
Bocheng Chen, Han Zi, Roucheng Ou +5
In the era of large language models (LLMs), attackers often manipulate natural language to elicit unsafe or harmful outputs, creating a new natural language attack surface unique t…
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…
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 \textit{well} and \textit{kind of}, are crucial components that enable LLMs to ``speak'' more like humans. They are used to convey emotions, intentions…
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…
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…