Boxuan Li retweeted
I want to share a new dataset of 331 reward-hackable environments. These are real environments used in Terminal Bench and adjacent benchmarks. I first got interested in this because, as a reviewer of Terminal Bench, I noticed a lot of our tasks were hackable. I also noticed that many contributors to the benchmark do so because it provides credibility when selling environments to labs. Hence, TBench tasks are, in my opinion, held to a higher quality standard than those being used today for RL. No one is spending hours manually reviewing the $1B in tasks being purchased by major labs. As far as I understand, while everyone knows environments are hackable, nobody has released hundreds of "realistic" environments. (link in comment)
Boxuan Li retweeted
Releasing the official SkyRL + Harbor integration: a standardized way to train terminal-use agents with RL.
From the creators of Terminal-Bench, Harbor is a widely adopted framework for evaluating terminal-use agents on any task expressible as a Dockerfile + instruction + test script.
This integration extends it: the same tasks you evaluate on, you can now RL-train on.
Blog: novasky-ai.notion.site/skyrl…
🧵
Boxuan Li retweeted
Been trying to keep up with how people are using Harbor. Breaking out my random gdoc into a public collection. Benchmarks, RL on harbor, training datasets, QA tools.
Really impressed with the community so far and excited to see what else gets made (add your project in a PR!).
github.com/harbor-framework/…
Boxuan Li retweeted
How can we make a better TerminalBench agent?
Today, we are announcing the OpenThoughts-Agent project.
OpenThoughts-Agent v1 is the first TerminalBench agent trained on fully open curated SFT and RL environments.
OpenThinker-Agent-v1 is the strongest model of its size on TerminalBench, and sets a new bar on our newly released OpenThoughts-TB-Dev benchmark. (1/n)
Boxuan Li retweeted
Super stoked about cline-bench! This is exactly the kind of thing we built Harbor for 🙏
We are announcing cline-bench, a real world open source benchmark for agentic coding.
cline-bench is built from real world engineering tasks from participating developers where frontier models failed and humans had to step in.
Each accepted task becomes a fully reproducible RL environment with a starting repo snapshot, a real prompt, and ground truth tests from the code that ultimately shipped.
For labs and researchers, this means:
> you can eval models on genuine engineering work, not leetcode puzzles.
> you get environments compatible with Harbor and modern eval tooling for side by side comparison.
> you can use the same tasks for SFT and RL so training and evaluation stay grounded in real engineering workflows.
Today we are opening contributions and starting to collect tasks through the Cline Provider. Participation is optional and limited to open source repos.
When a hard task stumps a model and you intervene, that failure can be turned into a standardized environment that the entire community can study, benchmark, and train on.
If you work on difficult open source problems, especially commercial OSS, I would like to personally invite you to help. We're committing $1M to sponsor open source maintainers to take part in the cline-bench initiative.
"Cline-bench is a great example of how open, real-world benchmarks can move the whole ecosystem forward. High-quality, verified coding tasks grounded in actual developer workflows are exactly what we need to meaningfully measure frontier models, uncover failure modes, and push the state of the art."
– @shyamalanadkat, Head of Applied Evals @OpenAI
"Nous Research is focused on training and proliferating models that excel at real world tasks. cline-bench will be an integral tool in our efforts to maximize the performance and understand the capabilities of our models."
– @Teknium, Head of Post Training @nousresearch
"We are huge fans of everything Cline has been doing to empower the open source AI ecosystem, and are incredibly excited to support the cline-bench release. High-quality open environments for agentic coding are exceedingly rare. This release will go a long way both as an evaluation of capabilities and as a post-training testbed for challenging real-world tasks, advancing our collective understanding and capabilities around autonomous software development."
– @willcb, Research Lead @PrimeIntellect:
"We share Cline's commitment to open source and believe making this benchmark available to all will help us continue to push the frontier coding capabilities of our LLMs."
– @b_roziere, Research Scientist @MistralAI:
Full details are in the blog:
cline.bot/blog/cline-bench-i…
Boxuan Li retweeted
Today, we’re announcing the next chapter of Terminal-Bench with two releases:
1. Harbor, a new package for running sandboxed agent rollouts at scale
2. Terminal-Bench 2.0, a harder version of Terminal-Bench with increased verification
Boxuan Li retweeted
We have a new state-of-the-art result on TheAgentCompany from Shanghai AI lab: MUSE + Gemini 2.5, solving 41.1% of the real-world inspired tasks.
The new method is based on "learning on the job", a memory-based method.
Boxuan Li retweeted
We just updated the leaderboard of TheAgentCompany, a benchmark of tasks like real-world work.
- In December 2024, 24% of the tasks could be solved
- In June 2025, 33% of the tasks could be solved
I'm interested to see when we'll be at 50%.
Boxuan Li retweeted
Can we design AI Agents that achieve generalizability across diverse task domains?
Our new paper introduces OpenHands-Versa, a generalist agent with strong performance on three challenging agent benchmarks, ranking #1 on SWE-Bench Multimodal and The Agent Company leaderboards 🚀
Boxuan Li retweeted
How far are we from having competent AI co-workers that can perform tasks as varied as software development, project management, administration, and data science?
In our new paper, we introduce TheAgentCompany, a benchmark for AI agents on consequential real-world tasks.
Boxuan Li retweeted
The JanusGraph Technical Steering Committee is excited to announce the release of JanusGraph 1.0.0 🎉
The release artifacts can be found at this location:
github.com/JanusGraph/janusg…
Thank you to all of the contributors!
#graphdatabase #graph #database #JanusGraph #TinkerPop
Boxuan Li retweeted
JanusGraph 0.6.4 has been released recently. This is a maintenance release that includes a lot of dependency updates, but also some bug fixes:
github.com/JanusGraph/janusg…
Also stay tuned, 1.0.0 release is coming soon!























