Sheng Li

Senior Principal Scientist@Oracle·美国·OpenReview

研究方向

Large Language Models · Trustworthy Artificial Intelligence · Graph neural networks · Continual Learning · Causal inference · Multi-view learning · Transfer Learning · Domain adaptation

Sheng Li

Finding the Cracks: Improving LLMs Reasoning with Paraphrastic Probing and Consistency Verification

Alignment-Weighted DPO: A principled reasoning approach to improve safety alignment

LLMs Are Too Smart to Be Average: Controlling LLM Proficiency via Guided Decoding

ItinBench: Benchmarking Planning Across Multiple Cognitive Dimensions with Large Language Models

Revisiting Dynamic Graphs from the Perspective of Time Series

COMPASS: Enhancing Agent Long-Horizon Reasoning with Evolving Context

BEACON: Bayesian Optimal Stopping for Efficient LLM Sampling

Improve Temporal Reasoning in Multimodal Large Language Models via Video Contrastive Decoding

Mind Control through Causal Inference: Predicting Clean Images from Poisoned Data

Benign Samples Matter! Fine-tuning On Outlier Benign Samples Severely Breaks Safety

BalancEdit: Dynamically Balancing the Generality-Locality Trade-off in Multi-modal Model Editing

Backdoor in Seconds: Unlocking Vulnerabilities in Large Pre-trained Models via Model Editing

No Free Lunch: Retrieval-Augmented Generation Undermines Fairness in LLMs, Even for Vigilant Users

BalancEdit: Dynamically Balancing the Generality-Locality Trade-off in Multi-modal Model Editing