Skip to content

Update news in March #522

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
chenyushuo merged 1 commit into from
Mar 31, 2026
+10 −6
Merged

Update news in March #522

Show file tree
Hide file tree
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
8 changes: 5 additions & 3 deletions README.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -32,6 +32,8 @@ Trinity-RFT provides functionalities for users with different backgrounds and ob

## 🚀 News

* [2026-03] 🤖 Trinity-RFT empowers the training of CoPaw-Flash, building a small agent model better suited for localized scenarios. Feel free to try CoPaw-Flash on [CoPaw](https://github.com/agentscope-ai/CoPaw); models are also available on [ModelScope](https://www.modelscope.cn/organization/AgentScope) and [HuggingFace](https://huggingface.co/agentscope-ai) ([News](https://mp.weixin.qq.com/s/-BXNU_PMi6QJuwSB5BqTbQ)).
* [2026-03] Trinity-RFT now supports Qwen3.5 series.
* [2026-02] [[Release Notes]](https://github.com/agentscope-ai/Trinity-RFT/releases/tag/v0.5.1) Trinity-RFT v0.5.1 released: Enhanced VLM support, logging improvements, bug fixes.
* [2026-02] [[Release Notes]](https://github.com/agentscope-ai/Trinity-RFT/releases/tag/v0.5.0) Trinity-RFT v0.5.0 released: colocate mode for single-GPU scenarios, trainer driven weight synchronization, automatic parallelism setting suggestion, and more.
* [2026-01] 🎉 Three papers accepted by ICLR 2026: [CHORD](https://github.com/agentscope-ai/Trinity-RFT/tree/main/examples/mix_chord), [BOTS](https://github.com/agentscope-ai/Trinity-RFT/tree/main/examples/bots), and [Group-relative REINFORCE variants](https://github.com/agentscope-ai/Trinity-RFT/tree/main/examples/rec_gsm8k). Try out these new algorithms in Trinity-RFT!
Expand All @@ -40,12 +42,12 @@ Trinity-RFT provides functionalities for users with different backgrounds and ob
* [2025-12] [[Release Notes]](https://github.com/agentscope-ai/Trinity-RFT/releases/tag/v0.4.0) Trinity-RFT v0.4.0 released: added [Tinker](https://thinkingmachines.ai/tinker/) backend for users **without GPUs**, add more benchmarks, enhance online RL and more.
* [2025-12] Trinity-RFT powers the medical and health business of "Taobao Shangou", enabling the AI agent to understand vague symptoms, proactively ask follow-up questions, and provide precise recommendations ([News](https://tech.china.com.cn/sx/20251201/411376.shtml)).
* [2025-11] Introducing [Learn-to-Ask](https://github.com/agentscope-ai/Trinity-RFT/tree/main/examples/learn_to_ask): a framework for training proactive dialogue agents from offline expert data ([paper](https://arxiv.org/pdf/2510.25441)).
* [2025-11] Introducing [BOTS](https://github.com/agentscope-ai/Trinity-RFT/tree/main/examples/bots): online RL task selection for efficient LLM fine-tuning ([paper](https://arxiv.org/pdf/2510.26374)).
* [2025-09] [Our paper](https://arxiv.org/pdf/2509.24203) reveals a novel off-policy interpretation for group-relative REINFORCE and its variants like GRPO and AsymRE ([implementation](https://github.com/agentscope-ai/Trinity-RFT/tree/main/examples/rec_gsm8k)).
* [2025-08] Introducing [CHORD](https://github.com/agentscope-ai/Trinity-RFT/tree/main/examples/mix_chord): dynamic SFT + RL integration for advanced LLM fine-tuning ([paper](https://arxiv.org/pdf/2508.11408)).

<details><summary> More... </summary>
<ul>
<li> [2025-11] Introducing [BOTS](https://github.com/agentscope-ai/Trinity-RFT/tree/main/examples/bots): online RL task selection for efficient LLM fine-tuning ([paper](https://arxiv.org/pdf/2510.26374)).</li>
<li> [2025-09] [Our paper](https://arxiv.org/pdf/2509.24203) reveals a novel off-policy interpretation for group-relative REINFORCE and its variants like GRPO and AsymRE ([implementation](https://github.com/agentscope-ai/Trinity-RFT/tree/main/examples/rec_gsm8k)).</li>
<li> [2026-03] [2025-08] Introducing [CHORD](https://github.com/agentscope-ai/Trinity-RFT/tree/main/examples/mix_chord): dynamic SFT + RL integration for advanced LLM fine-tuning ([paper](https://arxiv.org/pdf/2508.11408)).</li>
<li> [2025-11] Trinity-RFT v0.3.3 released: bug fixes.</li>
<li> [2025-11] Trinity-RFT v0.3.2 released: bug fixes and advanced task selection & scheduling.</li>
<li> [2025-10] Trinity-RFT v0.3.1 released: multi-stage training support, improved agentic RL examples, LoRA support, debug mode and new RL algorithms.</li>
Expand Down
8 changes: 5 additions & 3 deletions README_zh.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -41,6 +41,8 @@ Trinity-RFT 面向不同背景和目标的用户提供相应功能：

## 🚀 新闻

* [2026-03] 🤖 Trinity-RFT 助力 CoPaw-Flash 训练，打造更懂本地化场景的智能体小模型。欢迎到 [CoPaw](https://github.com/agentscope-ai/CoPaw) 试用 CoPaw-Flash，模型下载请见 [ModelScope](https://www.modelscope.cn/organization/AgentScope) 和 [HuggingFace](https://huggingface.co/agentscope-ai)（[新闻](https://mp.weixin.qq.com/s/-BXNU_PMi6QJuwSB5BqTbQ)）。
* [2026-03] Trinity-RFT 现在已经支持 Qwen3.5 系列模型。
* [2026-02] [[发布说明]](https://github.com/agentscope-ai/Trinity-RFT/releases/tag/v0.5.1) Trinity-RFT v0.5.1 发布：增强 VLM 支持，改进日志系统，修复若干 Bug。
* [2026-02] [[发布说明]](https://github.com/agentscope-ai/Trinity-RFT/releases/tag/v0.5.0) Trinity-RFT v0.5.0 发布：单 GPU 场景下的 colocate 模式，trainer 驱动的权重同步，自动并行设置建议等新功能。
* [2026-01] 🎉 三篇论文被 ICLR 2026 接收：[CHORD](https://github.com/agentscope-ai/Trinity-RFT/tree/main/examples/mix_chord)、[BOTS](https://github.com/agentscope-ai/Trinity-RFT/tree/main/examples/bots) 和 [Group-relative REINFORCE 系列变种](https://github.com/agentscope-ai/Trinity-RFT/tree/main/examples/rec_gsm8k)。在 Trinity-RFT 中尝试这些新算法吧！
Expand All @@ -50,12 +52,12 @@ Trinity-RFT 面向不同背景和目标的用户提供相应功能：
* [2025-12] Trinity-RFT 助力淘宝闪购医药健康业务，让 AI 智能体能够理解模糊症状、主动询问后续问题，并提供精准推荐（[新闻](https://tech.china.com.cn/sx/20251201/411376.shtml)）。
* [2025-11] [[发布说明](https://github.com/agentscope-ai/Trinity-RFT/releases/tag/v0.3.3)] Trinity-RFT v0.3.3 发布：修复若干 Bug。
* [2025-11] 推出 [Learn-to-Ask](https://github.com/agentscope-ai/Trinity-RFT/tree/main/examples/learn_to_ask)：利用离线专家数据，训练具备主动问询能力的对话智能体（[论文](https://arxiv.org/pdf/2510.25441)）。
* [2025-11] 推出 [BOTS](https://github.com/agentscope-ai/Trinity-RFT/tree/main/examples/bots)：在线 RL 任务选择，实现高效 LLM 微调（[论文](https://arxiv.org/pdf/2510.26374)）。
* [2025-09] 我们的 [论文](https://arxiv.org/pdf/2509.24203) 揭示了 group-relative REINFORCE 及其变种（如 GRPO 和 AsymRE）的 off-policy 解释（[代码](https://github.com/agentscope-ai/Trinity-RFT/tree/main/examples/rec_gsm8k)）。
* [2025-08] 推出 [CHORD](https://github.com/agentscope-ai/Trinity-RFT/tree/main/examples/mix_chord)：动态 SFT + RL 集成，实现进阶 LLM 微调（[论文](https://arxiv.org/pdf/2508.11408)）。

<details><summary> More... </summary>
<ul>
<li> [2025-11] 推出 [BOTS](https://github.com/agentscope-ai/Trinity-RFT/tree/main/examples/bots)：在线 RL 任务选择，实现高效 LLM 微调（[论文](https://arxiv.org/pdf/2510.26374)）。</li>
<li> [2025-09] 我们的 [论文](https://arxiv.org/pdf/2509.24203) 揭示了 group-relative REINFORCE 及其变种（如 GRPO 和 AsymRE）的 off-policy 解释（[代码](https://github.com/agentscope-ai/Trinity-RFT/tree/main/examples/rec_gsm8k)）。 </li>
<li> [2025-08] 推出 [CHORD](https://github.com/agentscope-ai/Trinity-RFT/tree/main/examples/mix_chord)：动态 SFT + RL 集成，实现进阶 LLM 微调（[论文](https://arxiv.org/pdf/2508.11408)）。</li>
<li> [2025-11] Trinity-RFT v0.3.2 发布：修复若干 Bug 并支持进阶的任务选择和调度。</li>
<li> [2025-10] Trinity-RFT v0.3.1 发布：多阶段训练支持、改进的智能体 RL 示例、LoRA 支持、调试模式和全新 RL 算法。</li>
<li> [2025-09] Trinity-RFT v0.3.0 发布：增强的 Buffer、FSDP2 & Megatron 支持，多模态模型，以及全新 RL 算法/示例。</li>
Expand Down
Loading