Showing 1–19 of 19 results
/ Date/ Name
May 17, 2024Adaptive Feature-based Low-Rank Compression of Large Language Models via Bayesian OptimizationOct 23, 2024Beware of Calibration Data for Pruning Large Language ModelsJan 5, 2025A Survey of Test-Time Compute: From Intuitive Inference to Deliberate ReasoningMay 28, 2019Amalgamating Filtered Knowledge: Learning Task-customized Student from Multi-task TeachersApr 23, 2019Student Becoming the Master: Knowledge Amalgamation for Joint Scene Parsing, Depth Estimation, and MoreJul 6, 2025GradOT: Training-free Gradient-preserving Offsite-tuning for Large Language ModelsMar 10, 2026GAST: Gradient-aligned Sparse Tuning of Large Language Models with Data-layer SelectionApr 29, 2026When to Vote, When to Rewrite: Disagreement-Guided Strategy Routing for Test-Time ScalingMar 20, 2020Data-Free Knowledge Amalgamation via Group-Stack Dual-GANDec 2, 2024CPRM: A LLM-based Continual Pre-training Framework for Relevance Modeling in Commercial SearchJun 3, 2024Demonstration Augmentation for Zero-shot In-context LearningDec 17, 2024Boosting LLM-based Relevance Modeling with Distribution-Aware Robust LearningMay 9, 2024OpenBA-V2: Reaching 77.3% High Compression Ratio with Fast Multi-Stage PruningApr 25, 2023Test-Time Adaptation with Perturbation Consistency LearningNov 24, 2025Think Before You Prune: Selective Self-Generated Calibration for Pruning Large Reasoning ModelsOct 22, 2024IPL: Leveraging Multimodal Large Language Models for Intelligent Product ListingApr 28, 2025Taming the Titans: A Survey of Efficient LLM Inference ServingApr 8, 2026When Is Thinking Enough? Early Exit via Sufficiency Assessment for Efficient ReasoningApr 9, 2026When to Trust Tools? Adaptive Tool Trust Calibration For Tool-Integrated Math Reasoning