7 papers
ICCU: In-Context Continual Unlearning via Pattern-Induced Refusal Rules
Ruihao Pan, Suhang Wang
Machine unlearning aims to remove the influence of specific data from trained language models. In real-world deployments, unlearning requests often arrive sequentially, which chall…
Slipstream: Trajectory-Grounded Compaction Validation for Long-Horizon Agents
Zhuofu Chen, Rui Pan, Yinwei Dai +1
To cope with the large contexts that long-horizon LLM agents produce, modern frameworks increasingly rely on compaction -- invoking an LLM to rewrite the accumulated trajectory int…
A Comprehensive Evaluation of LLM Unlearning Robustness under Multi-Turn Interaction
Ruihao Pan, Suhang Wang
Machine unlearning aims to remove the influence of specific training data from pre-trained models without retraining from scratch, and is increasingly important for large language…
METIS: Fast Quality-Aware RAG Systems with Configuration Adaptation
Siddhant Ray, Rui Pan, Zhuohan Gu +5
RAG (Retrieval Augmented Generation) allows LLMs (large language models) to generate better responses with external knowledge, but using more external knowledge often improves gene…
SpecReason: Fast and Accurate Inference-Time Compute via Speculative Reasoning
Rui Pan, Yinwei Dai, Zhihao Zhang +3
Recent advances in inference-time compute have significantly improved performance on complex tasks by generating long chains of thought (CoTs) using Large Reasoning Models (LRMs).…
Marconi: Prefix Caching for the Era of Hybrid LLMs
Rui Pan, Zhuang Wang, Zhen Jia +5
Hybrid models that combine the language modeling capabilities of Attention layers with the efficiency of Recurrent layers (e.g., State Space Models) have gained traction in practic…