Skip to content

(docs): update readme. #194

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
PanAndy merged 1 commit into from
Oct 14, 2025
Merged

(docs): update readme. #194

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
4 changes: 3 additions & 1 deletion README.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -40,7 +40,8 @@ Leveraging a multi-role distributed architecture with Ray for flexible resource

| 📣 Updates |
|:----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| **[09/28/2025]** 🎉 Ascend NPU support — see [usage guide](https://alibaba.github.io/ROLL/docs/English/UserGuide/ascend/ascend_usage). |
| **[10/14/2025]** 🎉 Our Paper released, see [Part II: ROLL Flash -- Accelerating RLVR and Agentic Training with Asynchrony](https://arxiv.org/abs/2510.11345), the code will be released soon. |
| **[09/28/2025]** 🎉 Ascend NPU support — see [usage guide](https://alibaba.github.io/ROLL/docs/English/UserGuide/ascend/ascend_usage). |
| **[09/25/2025]** 🎉 Our Paper released, see [RollPacker: Mitigating Long-Tail Rollouts for Fast, Synchronous RL Post-Training](https://arxiv.org/abs/2509.21009) |
| **[09/24/2025]** 🎉 Support [Wan2_2 Reward FL pipeline](examples/wan2.2-14B-reward_fl_ds/reward_fl_config.yaml). Explore the new capabilities! |
| **[09/23/2025]** 🎉 ROLL aligns with GEM environment definition, providing agentic Tool Use training capabilities, [ToolUse docs](docs_roll/docs/English/UserGuide/agentic/Tool_Use.md). |
Expand Down Expand Up @@ -157,6 +158,7 @@ We are continuously working to expand ROLL's capabilities:
---

## 🏆 Notable work based on ROLL
- [TaoSR-SHE](https://arxiv.org/abs/2510.07972): Stepwise Hybrid Examination Reinforcement Learning Framework for Taobao Search Relevance, with SRPO (hybrid reward model + offline verifier), diversified data filtering, and multi-stage curriculum learning.
- [EARL](https://arxiv.org/abs/2510.05943): Efficient Agentic RL Systems for LLMs, introducing a dynamic parallelism selector and a layout-aware data dispatcher to boost throughput, reduce memory and data movement bottlenecks, enabling stable large-scale agentic RL without hard context-length limits.
- [LiveThinking](https://arxiv.org/abs/2510.07685): Real-time reasoning for AI-powered livestreaming by distilling a 670B teacher LLM to a 30B MoE (3B active) via Rejection Sampling Fine-Tuning, then compressing reasoning with GRPO; delivers sub-second latency and ~30x compute reduction, with gains in response correctness (3.3%), helpfulness (21.8%), and GMV in Taobao Live Digital Live Service.
- [TaoSR-AGRL](https://www.arxiv.org/abs/2510.08048): Adaptive Guided Reinforcement Learning for LLM-based e-commerce relevance, introducing Rule-aware Reward Shaping and Adaptive Guided Replay to improve long-horizon reasoning, rule adherence, and training stability in Taobao Search; deployed in main search handling hundreds of millions of users.
Expand Down