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Reinforcement Learning via Self-Distillation
or, The Student Becomes the Master
16 hrs ago • Tim Dingman
EdgeBench: Unveiling Scaling Laws of Learning from Real-World Environments
or, Learning to Learn From Experience
Jul 22 • Tim Dingman
RLAnything + OpenClaw-RL
Originally presented as a live talk on March 25, 2026
Jul 20 • Tim Dingman
DSpark: Confidence-Scheduled Speculative Decoding with Semi-Autoregressive Generation
or, Diffusion in Production
Jul 17 • Tim Dingman
mHC vs Attention Residuals
Originally presented as a live talk on April 1, 2026
Jul 13 • Tim Dingman
OSWorld 2.0: Benchmarking Computer Use Agents on Long-Horizon Real-World Tasks
or, The Year of CUA
Jul 8 • Tim Dingman
DeepSeek-V4: Towards Highly Efficient Million-Token Context Intelligence
or, Necessity Is the Mother of Invention
Jul 6 • Tim Dingman
Qwen-AgentWorld: Language World Models for General Agents
or, A Mirror for Agents
Jul 1 • Tim Dingman

June 2026

ZAYA1-8B Technical Report
or, Swapping Space for Time
Jun 29 • Tim Dingman
Agents’ Last Exam
or, Benchmarks Are Hard
Jun 24 • Tim Dingman
Rewarding the Rare: Uniqueness-Aware RL for Creative Problem Solving in LLMs
or, Fox Math
Jun 22 • Tim Dingman
Nemotron 3 Ultra
or, The American Open-Weights King
Jun 18 • Tim Dingman
© 2026 Tim Dingman · Privacy ∙ Terms ∙ Collection notice
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