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Machine Learning
General machine learning — algorithms, architectures, optimization, theory. The broad arXiv category that papers without a more specific home tend to land in.
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Eliciting Weak-to-Strong Generalization with On-Policy Reverse Distillation
LLM Training · Sep 8 · 7:52
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Online Draft Co-Training for Speculative Decoding in Large-Scale, Long-Context RL Post-Training
Inference Optimization · Sep 7
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Train Smarter, Not Harder: Switching Signal-Guided Training in Active Learning
Evaluation · Sep 6
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BeaconKV: Key-Value Cache Compression Guided by Beacon Queries for Efficient Large Reasoning Model Inference
Inference Optimization · Sep 4
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Causal Foundation Models
Evaluation · Sep 2 · 7:23
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Verify Before You Distill: Prompt-Level Teacher Gating for On-Policy Distillation
Code Generation · Sep 2 · 6:50
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Cliff: Learning Process Rewards from the First Mistake
Reasoning · Sep 2
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CRISP: Cliff-awaRe Input-adaptive Sparse Prefilling with Structural-Mass-Motivated Routing
Inference Optimization · Sep 1
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LatentPress: Context Compression Beyond Text and Vision
Inference Optimization · Sep 1
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SMELT: Scaling Laws for Compute-Matched MoE Looped Transformers
Inference Optimization · Sep 1 · 7:18
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