From the 1 of 8 linked papers with an AI index.
8 papers
Generative Learning for Quantum Measurement Design
Jun Dai, Olivier Nahman-Lévesque, Guillaume Rabusseau +2
Extracting quantum information from a quantum state is a fundamental task of quantum computation, often requiring the estimation of many non-commuting observables under a finite me…
OmniDelta: Skill-Driven Budget Allocation for Token Compression in OmniLLMs
Haoyang Huang, Wenjie Huang, Tianqi Xu +14
OmniDelta is a training-free framework that dynamically allocates token budgets for audio and video inputs in omni-modal large language models, using skill pools and local complexi…
Backend-Aware Graph Learning for Denoising Outcome Distributions in Quantum Program Testing
Ning Ma, Jun Dai, Heng Li
Testing quantum programs on NISQ (Noisy Intermediate-Scale Quantum) backends is challenging because the noise disturbs outcome distributions and can affect pass/fail decisions. We…
Discrete Flow-Based Generative Models for Measurement Optimization in Quantum Computing
Isaac L. Huidobro-Meezs, Jun Dai, Rodrigo A. Vargas-Hernández
Achieving chemical accuracy in quantum simulations is often constrained by the measurement bottleneck: estimating operators requires a large number of shots, which remains costly e…
Draft Less, Retrieve More: Hybrid Tree Construction for Speculative Decoding
Yuhao Shen, Tianyu Liu, Xinyi Hu +9
Speculative decoding (SD) accelerates large language model inference by leveraging a draft-then-verify paradigm. To maximize the acceptance rate, recent methods construct expansive…
ECHO: Elastic Speculative Decoding with Sparse Gating for High-Concurrency Scenarios
Xinyi Hu, Yuhao Shen, Baolin Zhang +6
Speculative Decoding promises to accelerate the inference of Large Language Models, yet its efficacy often degrades in production-grade serving. Existing evaluations typically over…