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20242026
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cs.CL2026

KaLM-Reranker-V1: Fast but Not Late Interaction for Compressed Document Reranking

Xinping Zhao, Jiaxin Xu, Ziqi Dai +7

As retrieval systems scale, high-quality reranking becomes increasingly important. However, most existing rerankers, whether encoder-based or decoder-based, jointly encode the quer…

cs.CL2026

Less Languages, Less Tokens: An Efficient Unified Logic Cross-lingual Chain-of-Thought Reasoning Framework

Chenyuan Zhang, Qiguang Chen, Xie Chen +6

Cross-lingual chain-of-thought (XCoT) with self-consistency markedly enhances multilingual reasoning, yet existing methods remain costly due to extensive sampling of full trajector…

cs.CL2026

Dynamic Long Context Reasoning over Compressed Memory via End-to-End Reinforcement Learning

Zhuoen Chen, Dongfang Li, Meishan Zhang +2

Large Language Models (LLMs) face significant challenges in long-context processing, including quadratic computational costs, information forgetting, and the context fragmentation…

cs.CL2026

LycheeDecode: Accelerating Long-Context LLM Inference via Hybrid-Head Sparse Decoding

Gang Lin, Dongfang Li, Zhuoen Chen +4

The proliferation of long-context large language models (LLMs) exposes a key bottleneck: the rapidly expanding key-value cache during decoding, which imposes heavy memory and laten…

cs.CL2025

Vision Enhancing LLMs: Empowering Multimodal Knowledge Storage and Sharing in LLMs

Yunxin Li, Zhenyu Liu, Baotian Hu +4

Recent advancements in multimodal large language models (MLLMs) have achieved significant multimodal generation capabilities, akin to GPT-4. These models predominantly map visual i…

cs.CL2025

KaLM-Embedding-V2: Superior Training Techniques and Data Inspire A Versatile Embedding Model

Xinping Zhao, Xinshuo Hu, Zifei Shan +14

Recent advancements in Large Language Models (LLMs)-based text embedding models primarily focus on data scaling or synthesis, yet limited exploration of training techniques and dat…