Pretty cool people are being added to the LLM Agent & LLM Reasoning group. Thanks @lisaalaz.bsky.social for suggesting @jhamrick.bsky.social @gabepsilon.bsky.social and others.
Feel free to mention yourself and others. :)
go.bsky.app/LUrLWXe
#LLMAgents #LLMReasoning
Nice starter pack! Would love to be added. I develop LLM agent benchmarks (workarena, browsergym) and tools to design LLM agents.
See x.com/alex_lacoste...
Or x.com/alex_lacoste...
We’re really excited to release this large collaborative work for unifying web agent benchmarks under the same roof.
In this TMLR paper, we dive in-depth into #BrowserGym and #AgentLab. We also present some unexpected performances from Claude 3.5-Sonnet
I finally created my first starter pack for #buildinpublic #indiehacker and #founder who are building in the AI Agent Space
If you are building AI agents stuff, I'd be happy to include you in 😁
💡 Share what you're building in the comment
🧡 Like and repost for visibility
go.bsky.app/JPx5hfV
Would love to be added :)
I build web agents, in particular open-source packages for developing and evaluating web agents.
e.g. x.com/alex_lacoste...
I've created a starter pack of researchers working on digital agents (focusing on web, mobile and OS agents).
I am missing a lot, and many are not on bsky yet, so if I missed you or someone you know, please send me a DM with the link to a relevant paper and I will update the starter pack!
I finally created my first starter pack for #buildinpublic #indiehacker and #founder who are building tools related to AI and LLM.
If you are building AI stuff, I'd be happy to include you in 😁
💡 Share what you're building in the comment
🧡 Like and repost for visibility
go.bsky.app/UcofkF4
Would love to be added :)
I build web agents, in particular open-source packages for developing and evaluating web agents.
e.g. x.com/alex_lacoste...
Would love to be added :)
I build web agents, in particular open-source packages for developing and evaluating web agents.
Hello! 1 year MILA alumni here ✋ would love to be added
AgentLab diagram. The image describes AgentLab, a framework for efficient parallel experiments with agents. It highlights: Core Agent Features: Dynamic Prompting and a Unified LLM API for interacting with large language models. BrowserGym Platform: A tool for testing agents on benchmarks like WebArena, WorkArena, MiniWoB, and others. Key Features: Reproducibility, a Unified Leaderboard, an analysis tool called Xray, and a Dataset for sharing agent traces. Blue elements represent AgentLab components.
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We are thrilled to release #AgentLab, a new open-source package for developing and evaluating web agents. This builds on the new #BrowserGym package which supports 10 different benchmarks, including #WebArena.