6 papers · 1 filter
LATTE: Forecasting Peer Anchored Preference Trajectories for Personalized LLM Generation
Jinze Li, Xiaoyan Yang, Shuo Yang +5
Personalized generation with frozen large language models requires a conditioning signal that is both compact and current. Existing personalization methods typically retrieve or su…
Beyond the Target: From Imitation to Collaboration in Speculative Decoding
Jinze Li, Yixing Xu, Guanchen Li +7
Speculative decoding (SPD) accelerates large language model (LLM) inference by letting a smaller draft model propose multiple future tokens that are verified in parallel by a large…
OCR-Memory: Optical Context Retrieval for Long-Horizon Agent Memory
Jinze Li, Yang Zhang, Xin Yang +5
Autonomous LLM agents increasingly operate in long-horizon, interactive settings where success depends on reusing experience accumulated over extended histories. However, existing…
Training-Free Loosely Speculative Decoding: Accepting Semantically Correct Drafts Beyond Exact Match
Jinze Li, Yixing Xu, Guanchen Li +6
Large language models (LLMs) achieve strong performance across diverse tasks but suffer from high inference latency due to their autoregressive generation. Speculative Decoding (SP…
RAMA: Retrieval-Augmented Multi-Agent Framework for Misinformation Detection in Multimodal Fact-Checking
Shuo Yang, Zijian Yu, Zhenzhe Ying +6
The rapid proliferation of multimodal misinformation presents significant challenges for automated fact-checking systems, especially when claims are ambiguous or lack sufficient co…
RealFactBench: A Benchmark for Evaluating Large Language Models in Real-World Fact-Checking
Shuo Yang, Yuqin Dai, Guoqing Wang +6
Large Language Models (LLMs) hold significant potential for advancing fact-checking by leveraging their capabilities in reasoning, evidence retrieval, and explanation generation. H…