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From the 2 of 19 linked papers with an AI index.

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19 papers

cs.CV2026

FeatFix: Reuse What You Verify through Local Exact-Feature Correction for Faster Cached Diffusion Inference

Hanshuai Cui, Zhiqing Tang, Zhi Yao +3

FeatFix reuses exact intermediate features computed for verification to locally correct draft outputs in cached diffusion inference, speeding up image and video generation while pr…

cs.AI2026

MemTxn: A Transaction Boundary for Source-Supported Updates and Complete-State Recovery in Agent Memory

Hanshuai Cui, Zhiqing Tang, Zhi Yao +3

MemTxn is a governance layer for large language model agents that adds a transaction boundary to verify source-supported memory updates, resolve conflicting facts, and recover a co…

cs.DC2026

LASER: Load-Aware Serving with Early-Exit for Reasoning LLMs at the Edge

Zhiqing Tang, Size Li, Hanshuai Cui +5

Large reasoning models (LRMs) such as DeepSeek-R1 have achieved strong performance through extended chain-of-thought (CoT) generation. However, deploying them on edge devices raise…

cs.DC2026

RISE: Relay Inference and Online Scheduling for Efficient Edge-Device Collaborative Diffusion Model Services

Zilan Huang, Zhiqing Tang, Hanshuai Cui +4

Text-to-image diffusion models are increasingly deployed at the network edge to serve heterogeneous workloads with diverse quality and latency requirements. However, existing deplo…

cs.IR2026

ConCise: Training-Free Conclusion-Chain State Compression for Cost-Efficient Multi-Step RAG Services

Kuan Yan, Zhiqing Tang, Tian Wang +1

Multi-step retrieval-augmented generation (RAG) has been widely deployed as LLM-powered web services for complex question answering, where iterative retrieval-reasoning rounds deli…

cs.AI2026

CogGuard: Cognitive and Operational Profiling for Proactive Warning in Edge Intelligent Services

Zhi Yao, Weihao Chen, Zhiqing Tang +4

Proactive warning is an important capability for edge intelligent services, where the system predicts whether a subject will successfully complete an incoming task under strict lat…