Huawei AI-Solver Group
Huawei AI-Solver Group
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Mingxuan Yuan
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Accelerating Large Language Model Reasoning via Speculative Search
ARS: Automatic Routing Solver with Large Language Models
Certifying Language Model Robustness with Fuzzed Randomized Smoothing: An Efficient Defense Against Backdoor Attacks
CMoE: Fast Carving of Mixture-of-Experts for Efficient LLM Inference
Fitness Landscape of Large Language Model-Assisted Automated Algorithm Search
Harnessing Large Language Models Locally: Empirical Results and Implications for AI PC
HyperTree Planning: Enhancing LLM Reasoning via Hierarchical Thinking
KVTuner: Sensitivity-Aware Layer-wise Mixed Precision KV Cache Quantization for Efficient and Nearly Lossless LLM Inference
Large language model for multiobjective evolutionary optimization
PASER: Post-Training Data Selection for Efficient Pruned Large Language Model Recovery
PreMoe: Lightening MoEs on Constrained Memory by Expert Pruning and Retrieval
TrimR: Verifier-based Training-Free Thinking Compression for Efficient Test-Time Scaling
A systematic survey on large language models for algorithm design
Betterv: Controlled verilog generation with discriminative guidance
DiffSAT: Differential MaxSAT Layer for SAT Solving
FuseGPT: Learnable Layers Fusion of Generative Pre-trained Transformers
Grass: Combining graph neural networks with expert knowledge for sat solver selection
IB-Net: Initial Branch Network for Variable Decision in Boolean Satisfiability
Layout decomposition via boolean satisfiability
Learning to cut via hierarchical sequence/set model for efficient mixed-integer programming
Neuroselect: Learning to select clauses in sat solvers
Parallel gröbner basis rewriting and memory optimization for efficient multiplier verification
The Graph's Apprentice: Teaching an LLM Low Level Knowledge for Circuit Quality Estimation
A survey for solving mixed integer programming via machine learning
Deepgate2: Functionality-aware circuit representation learning
Hardsatgen: Understanding the difficulty of hard sat formula generation and a strong structure-hardness-aware baseline
Learning cut selection for mixed-integer linear programming via hierarchical sequence model
Llm4eda: Emerging progress in large language models for electronic design automation
Machine learning methods in solving the boolean satisfiability problem
Satformer: transformer-based unsat core learning
Accelerate sat-based atpg via preprocessing and new conflict management heuristics
Accelerate the optimization of large-scale manufacturing planning using game theory
Bilevel learning for large-scale flexible flow shop scheduling
Branch ranking for efficient mixed-integer programming via offline ranking-based policy learning
Learning to select cuts for efficient mixed-integer programming
Neural fault analysis for sat-based atpg
Learning to optimize industry-scale dynamic pickup and delivery problems
Multiobjective optimization-aided decision-making system for large-scale manufacturing planning
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