Progressive RLVR paper says TinyLoRA and distillation are both necessary
ddkang · x · 2026-07-21
The thread reports an ablation study on Progressive RLVR and says every ingredient matters.
Key findings:
- Removing distillation and training directly with TinyLoRA makes the bound 15% looser.
- Replacing TinyLoRA with standard LoRA makes the bounds vacuous on the 4B model and meaningless on the 2B model.
- On Qwen3.5-4B across Math, Code, General Knowledge, and Text-to-SQL, the bounds are tight: they land within 8–13% of training accuracy and 17–51% above the base model.
The plot in the image compares Progressive RLVR and TinyLoRA/LoRA variants across quantization levels, showing Progressive w/ TinyLoRA tracking best among the bound methods.
More from Research
- Stanford Team Introduces Gigatoken, the World's Fastest Tokenizer — StanfordAILab · 2026-07-22
- Tabul AI launches Metal TreeSHAP to speed up Shapley values on Apple silicon — Scobleizer · 2026-07-22
- Reddit points to OpenAI’s ChatGPT Ads page — EcstaticAsparagus509 · 2026-07-22
- Open-source runtime lets each repo define its own AI code reviewer — ibabufrik · 2026-07-22
- DeepSWE: A New Benchmark for Evaluating AI Coding Agents on Real GitHub Issues — pmz · 2026-07-22
- A Rust space-economy sim runs hundreds of autonomous ships, built with Claude — kalcode · 2026-07-22