Papers by Zhongle Xie

2 papers
MM-ShiftKV: Decode-Aware Prefill-Stage KV Selection for Multimodal Large Language Models (2026.findings-acl)

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Challenge: Recent work suggests a prefill-stage KV cache selection method to estimate KV importance from prefilling statistics.
Approach: They propose a training-free, decode-aware and strictly prefill-only KV selection method that retains key-value caching for decoding .
Outcome: The proposed method outperforms existing methods under tight cache budgets on multimodal benchmarks.
TokenTiming: A Dynamic Alignment Method for Universal Speculative Decoding Model Pairs (2026.acl-long)

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Challenge: Speculative decoding (SD) is a useful tool for accelerating large language models . but its utility is limited by a fundamental constraint: draft and target models must share the same vocabulary .
Approach: They propose an algorithm that uses a draft token sequence to get a new target token sequence and then uses DTW to build a mapping to transfer probability distributions.
Outcome: The proposed method shows 1.57x speedup on various tasks.

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