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cs.CL2026

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…

cs.CL2026

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…

cs.CL2026

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…

cs.CL2026

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…

cs.CL2026

Reinforced Curriculum Pre-Alignment for Domain-Adaptive VLMs

Yuming Yan, Shuo Yang, Kai Tang +7

Vision-Language Models (VLMs) demonstrate remarkable general-purpose capabilities but often fall short in specialized domains such as medical imaging or geometric problem-solving.…

cs.CL2025

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…