8 papers · 1 filter
LatentRiskBench: Measuring State-Dependent Risks in Enterprise Agents
Jingyue Cong, Estrid He, Zhuang Li +5
Enterprise agents face safety risks that cannot be determined from individual actions alone. Existing safety benchmarks largely evaluate action-local risks, overlooking failures wh…
Decouple to Forget: Semantic Mediation for Sensitive Unlearning in Large Language Models
Jingyue Cong, Andy Song, Yang Yu +7
Machine unlearning for large language models seeks to remove specified knowledge while preserving general capability, yet current methods often treat an entire response as the unit…
GraphProfiler: Source-Linked Sensitive Attribute Inference via Personal Knowledge Graphs
Ahmed Sohair Khan, Estrid He, Chenglong Ma +2
Sensitive attributes such as age, income, and occupation can be inferred from user-generated content by aggregating indirect cues across many ordinary posts. LLM-based profilers ca…
I Am No One: Style-Aware Paraphrasing for Text Anonymization
Ahmed Sohair Khan, Estrid He, Monica Wachowicz +1
Authorship attribution models can re-identify users from seemingly anonymized text by exploiting stable stylistic fingerprints, even after explicit identifiers are removed, posing…
Twin Worlds: Equivariance-Based Abstention for Evidence-Grounded Reasoning
Vy Nguyen, Ziqi Xu, Jeffrey Chan +5
Knowledge-intensive reasoning requires Large Language Models (LLMs) to ground answers in provided evidence. When evidence is insufficient, it is desirable that models abstain rathe…
Hallucinate Less by Thinking More: Aspect-Based Causal Abstention for Large Language Models
Vy Nguyen, Ziqi Xu, Jeffrey Chan +3
Large Language Models (LLMs) often produce fluent but factually incorrect responses, a phenomenon known as hallucination. Abstention, where the model chooses not to answer and inst…
An Empirical Study of the Role of Incompleteness and Ambiguity in Interactions with Large Language Models
Riya Naik, Ashwin Srinivasan, Estrid He +1
Natural language as a medium for human-computer interaction has long been anticipated, has been undergoing a sea-change with the advent of Large Language Models (LLMs) with startli…
Deep Contrastive Unlearning for Language Models
Estrid He, Tabinda Sarwar, Ibrahim Khalil +2
The past a few years have witnessed the great success of large language models, demonstrating powerful capabilities in comprehending textual data and generating human-like language…