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Adaptive Context Parallelism for Production LLM Serving
Jiarui Guo, Rongle Wang, Peijun Huang +7
As LLM context windows expand and input sequences grow longer, serving systems face increasing computational and memory demands. Context parallelism (CP), which partitions the inpu…
InSituANN: Revisiting IVF for PCIe-Efficient Billion-Scale Vector Search
Yuemeng Xu, Zongxi Liu, Junyu Long +7
Approximate nearest neighbor search (ANNS) over billion-scale vector datasets has become a foundational operator for modern retrieval systems, powering large-scale recommendation,…
RTP-LLM: High-Performance Alibaba LLM Inference Engine
Boyu Tan, Jiarui Guo, Zongwei Lv +26
Large Language Models (LLMs) have revolutionized AI applications, but deploying them at scale presents significant challenges. We present RTP-LLM, a high-performance inference engi…
ReCALL: Recalibrating Capability Degradation for MLLM-based Composed Image Retrieval
Tianyu Yang, Chenwei He, Xiangzhao Hao +6
Composed Image Retrieval (CIR) aims to retrieve target images based on a hybrid query comprising a reference image and a modification text. Early dual-tower Vision-Language Models…
Rethinking Retrieval-Augmentation as Synthesis: A Query-Aware Context Merging Approach
Jiarui Guo, Yuemeng Xu, Zongwei Lv +6
Retrieval-Augmented Generation (RAG) enables Large Language Models (LLMs) to extend their existing knowledge by dynamically incorporating external information. However, practical d…
The Molecular Structure of Thought: Mapping the Topology of Long Chain-of-Thought Reasoning
Qiguang Chen, Yantao Du, Ziniu Li +10
Large language models (LLMs) often fail to learn effective long chain-of-thought (Long CoT) reasoning from human or non-Long-CoT LLMs imitation. To understand this, we propose that…