3 citations · 3 across the 5 of their papers we have counts for
7 papers
Soft Spatial Reasoning
Rafi Ibn Sultan, Md. Sajid Alam Chowdhury, Saleh Zare Zade +4
Large Vision-Language Models (LVLMs) commonly perform spatial reasoning through chain-of-thought (CoT), encoding intermediate reasoning as autoregressive sequences of discrete lang…
Towards Mitigating Deceptive Safety Alignment in Large Reasoning Models
Xiangyu Zhou, Saleh Zare Zade, Rafi Ibn Sultan +2
Large Reasoning Models (LRMs) are commonly trained with reinforcement learning (RL) to improve their generation of chain-of-thought (CoT) reasoning before producing final answers.…
Alignment of LRMs via Counter-Aligned Few-Shot Conversation Exposure
Xiangyu Zhou, Saleh Zare Zade, Dongxiao Zhu
Large Reasoning Models (LRMs) rely on explicit chain-of-thought (CoT) reasoning and large context windows to achieve strong performance on complex tasks, but these features also in…
Attention Smoothing Is All You Need For Unlearning
Saleh Zare Zade, Xiangyu Zhou, Sijia Liu +1
Large Language Models are prone to memorizing sensitive, copyrighted, or hazardous content, posing significant privacy and legal concerns. Retraining from scratch is computationall…
Not All Tokens Are Meant to Be Forgotten
Xiangyu Zhou, Yao Qiang, Saleh Zare Zade +3
Large Language Models (LLMs), pre-trained on massive text corpora, exhibit remarkable human-level language understanding, reasoning, and decision-making abilities. However, they te…
Automatic Calibration for Membership Inference Attack on Large Language Models
Saleh Zare Zade, Yao Qiang, Xiangyu Zhou +4
Membership Inference Attacks (MIAs) have recently been employed to determine whether a specific text was part of the pre-training data of Large Language Models (LLMs). However, exi…
Learning to Poison Large Language Models for Downstream Manipulation
Xiangyu Zhou, Yao Qiang, Saleh Zare Zade +4
The advent of Large Language Models (LLMs) has marked significant achievements in language processing and reasoning capabilities. Despite their advancements, LLMs face vulnerabilit…