Qingfeng Lan

Researcher @Alibaba_Qwen, PhD @rlai_lab. Ideas are my own.

[Qingfeng Lan @qingfeng_lan]

For long horizon tasks in LLM, PPO and GRPO are no longer suitable. Scaling off-policy algorithms will the next bet.

[Qingfeng Lan @qingfeng_lan]

@WenhuChen @ArminPCM Check out our loss of plasticity paper to find out: https://t.co/URynMy9Vc9

[Qingfeng Lan @qingfeng_lan]

Using AI doesn't magically turn NP problems into P problems.

[Qingfeng Lan @qingfeng_lan]

There are three wailing walls for intelligent systems: the exploration-exploitation dilemma, credit assignment, and continual learning.

[Qingfeng Lan @qingfeng_lan]

Qwen is nothing without its people. ❤️🥃

[Junyang Lin @JustinLin610]

me stepping down. bye my beloved qwen.

[Qingfeng Lan @qingfeng_lan]

# Made a small contribution
Putting in some extra hours on Chinese New Year's Eve – finally ready to enjoy the holidays!

[Qwen @Alibaba_Qwen]

🚀 Qwen3.5-397B-A17B is here: The first open-weight model in the Qwen3.5 series.

🖼️Native multimodal. Trained for real-world agents.
✨Powered by hybrid linear attention + sparse MoE and large-scale RL environment scaling.
⚡8.6x–19.0x decoding throughput vs Qwen3-Max
🌍201 languages & dialects
📜Apache2.0 licensed

🔗Dive in:
GitHub: https://t.co/NzNdS9joAT
Chat: https://t.co/bg4tAU0Rhw
API：https://t.co/YiiyKTnHoU
Qwen Code: https://t.co/qqwj5nAger
Hugging Face: https://t.co/wFMdX5p5um
ModelScope: https://t.co/9NGXcId57a
blog: https://t.co/AW8UQStXaL

[Qwen @Alibaba_Qwen]

🚀 Introducing Qwen3-Max-Thinking, our most capable reasoning model yet. Trained with massive scale and advanced RL, it delivers strong performance across reasoning, knowledge, tool use, and agent capabilities.
✨ Key innovations:
✅ Adaptive tool-use: intelligently leverages Search, Memory & Code Interpreter without manual selection
✅ Test-time scaling: multi-round self-reflection beats Gemini 3 Pro on reasoning
✅ From complex math (98.0 on HMMT Feb) to agentic search (49.8 on HLE)—it just thinks better.

🧠 Think deeper. Solve harder.
Try the adaptive reasoning experience now: https://t.co/V7RmqMaVNZ

Completions API:  https://t.co/Eo8DZdw4ac
Responses API:  https://t.co/ocUfhvT3M8

blog:  https://t.co/l7MYH3pgWm

[Qingfeng Lan @qingfeng_lan]

@tydsh Crazy.

[CoLLAs 2026 @CoLLAs_Conf]

📢 Just 8 weeks until #CoLLAs2025!

Modern ML thrives in benchmarks but struggles in the wild. CoLLAs is where we tackle non-stationarity head-on: catastrophic forgetting, distribution shift, continual RL, online adaptation, and lifelong learning for ML.

📍 Aug 11–14 @Penn

🧠 Keynotes, Workshops, tutorials, posters & community

🔗 https://t.co/8Yyt33Ef8h

#ContinualLearning #LifelongLearning #AI #MachineLearning

[Qingfeng Lan @qingfeng_lan]

🚀RL algorithms are shaping the post-training of LLMs, but how do their objectives connect? In this blog, I explore their relationships and provide a unified perspective through the Policy Gradient Theorem—the backbone of policy gradient methods.
Dive in: https://t.co/SQREPoqGH0

[Amii @AmiiThinks]

BREAKING: Amii Chief Scientific Advisor, Richard S. Sutton, has been awarded the A.M. Turing Award, the highest honour in computer science, alongside Andrew Barto! Read the official @TheOfficialACM announcement: https://t.co/JXDhdEsQv7

#TuringAward #AI #ReinforcementLearning

[CoLLAs 2026 @CoLLAs_Conf]

🚨 Call for Reviewers! 🚨

Want to contribute to advancing lifelong learning research? #CoLLAs2025 is looking for expert reviewers! 📝

Help shape the field by reviewing cutting-edge research in continual and lifelong learning.

🔗 Apply here: https://t.co/nP6oE2OwPl

#MachineLearning #LifelongLearning #ContinualLearning #AI #AcademicReview

[Mohamed Elsayed @mhmd_elsaye]

Would you believe that deep RL can work without replay buffers, target networks, or batch updates? Our recent work gets deep RL agents to learn from a continuous stream of data one sample at a time without storing any sample. Joint work with @Gautham529 and @rupammahmood.

[Gautham Vasan @Gautham529]

Our NeurIPS paper is now on arXiv:
We introduce Action Value Gradient (AVG), a novel incremental deep RL method that learns in real-time, one sample at a time — no batch updates, target networks or a replay buffer!

Co-authors @mhmd_elsaye @bellingerc @white_martha @rupammahmood

[Marlos C. Machado @MarlosCMachado]

RLC will be held at the Univ. of Alberta, Edmonton, in 2025. I'm happy to say that we now have the conference's website out: https://t.co/ZjpvWi5jyV

We'll continue to update it, and the CFP will be out soon, but the relevant dates are already there.

@RL_Conference @UAlberta

[CoLLAs 2026 @CoLLAs_Conf]

📢 Exciting News! The Fourth Conference on Lifelong Learning Agents (CoLLAs 2025) will be held at the University of Pennsylvania (@Penn) in Philadelphia, USA 🇺🇸

🗓️ Important Dates:

Abstract Deadline: Feb 21, 2025
Submission Deadline: Feb 26, 2025
Conference Dates: Aug 11 - Aug 14, 2025

We invite submissions that present new theories, methodologies, applications, or insights into algorithms and benchmarks designed for non-i.i.d. and non-stationary settings. Accepted papers will be published in the Proceedings of Machine Learning Research (PMLR). 📚

Full CFP: https://t.co/S8MwjLbOAr

#CoLLAs2025 #AI #MachineLearning #ContinualLearning #LifelongLearning #ResearchConference #CallForPapers #NonStationaryLearning

[Richard Sutton @RichardSSutton]

A year later and our work on Loss of Plasticity is finally published, in Nature no less! The Nature version is totally rewritten and has many new results:
https://t.co/QImypXpqQl
Congratulations to the authors:
@s_dohare
@JFernandoHG
@LanceLan3
@rahman_parash
@rupammahmood

[Amii @AmiiThinks]

It’s a deep learning problem that was ‘hidden in plain sight:’ A new Nature paper by Amii researchers explores why continual learning models can all of a sudden stop working, and what to do about it: https://t.co/WJ4Rgb8qoe #AI #ContinualLearning #MachineLearning

[Marlos C. Machado @MarlosCMachado]

I couldn't be prouder of my colleagues at the @UAlberta! The work led by @s_dohare, in collaboration w/ J. F. H.-Garcia, @LanceLan3, @rahman_parash, @rupammahmood, & @RichardSSutton on continual learning and loss of plasticity is now published at @Nature!

https://t.co/PaO8GPsVHq

[Qingfeng Lan @qingfeng_lan]

@anaik96 @mhmd_elsaye @RL_Conference @RichardSSutton nice catch!