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We are excited to announce CLIN 🤖: The first continually learning language agent that excels in both task adaptation and generalization to unseen tasks and environments in a pure zero-shot setup. Aristo Team at AI2 Ai2 Website: allenai.github.io/clin/ Let's dive in 🧵 (1/n)

(n/n) This was only possible with the huge team effort: bhavana dalvi, Peter Jansen ( @peterjansen-ai.bsky.social ), Oyvind, Niket, Li "Harry" Zhang, Chris Callison-Burch, and Peter Clark! CLIN is open source: github.com/allenai/clin Paper: arxiv.org/pdf/2310.10134…

Using a dynamic, persistent memory, CLIN is the first continually learning model that excels in both task adaptation & generalization to unseen tasks in a zero-shot setup. Explore this exciting new work by AI2's Bodhisattwa Majumder and bhavana dalvi, and the Aristo Team at AI2 team:

I am thrilled to share our work: Using a dynamic, persistent memory🧠 CLIN is the first continually learning model 🤖 that excels in both task adaptation & generalization to unseen tasks in a zero-shot setup 🧙 Bodhisattwa Majumder Ai2 Aristo Team at AI2 webpage: allenai.github.io/clin/

Excited to share our work, "Skill Set Optimization", a continual learning method for LLM actors that: - Automatically extracts modular subgoals to use as skills - Reinforces skills using environment reward - Facilitates skill retrieval based on state allenai.github.io/sso 🧵

Excited to share our work on Continual Learning via Skill Set Optimization🥳 Can a language agent explore new interactive tasks, automatically identify useful skills, generalize them to new tasks? allenai.github.io/sso with Kolby Nottingham Bodhisattwa Majumder Sameer Singh Peter Clark Roy Fox (@[email protected])

Is it possible to build end-to-end autonomous discovery systems using Large Generative Models (LGMs)? 🧬 In this position paper, we argue: arxiv.org/pdf/2402.13610… 🧵 (1/n) Ai2 Aristo Team at AI2 Harshit Surana UMass Amherst University of Utah

Excited to share our recent paper led by Nathaniel Weir 🥳 Enhancing Systematic Decompositional Natural Language Inference Using Informal Logic tinyurl.com/bdehyv5k Thanks to all the collaborators!

We ( Greg Durrett , bhavana dalvi , Peter Jansen ( @peterjansen-ai.bsky.social ) , Danilo Ribeiro @ ACL 2023 , Xi Ye , Wenting Zhao , Ben Lipkin , and Lionel Wong from CoCoSci MIT ) are excited to announce the 2nd Workshop on Natural Language Reasoning and Structured Explanations (NLRSE), co-located with ACL 2024. 🧵

CFP for NLRSE workshop@ACL coming up soon: Deadline May 17, 2024. Please submit your exciting work!

NLRSE workshop @ ACL 2024: Deadline extended to May 21! Also note that non-archival cross-submissions (papers accepted to other venues, such as ACL Findings) can be submitted on the Google Form here: docs.google.com/forms/d/1OAzZE…

We are thrilled to announce a benchmark for data-driven scientific hypothesis discovery. 🥳 Ai2 Aristo Team at AI2 Bodhisattwa Majumder Harshit Surana UMass Amherst

.Christopher Manning in the first keynote Conference on Language Modeling grazed over the meaning of true intelligence saying it involves real-time “adaptation” — but how do you do it? Learn our way of purely in-context continual learning for LLMs! Poster on Wed (4:30 EST) 🦙

Can language models perform end-to-end scientific discovery? In our NeurIPS Spotlight paper, we show: very rarely. Our best model found <20% of discoveries, our best PhDs found nearly all. Paper: arxiv.org/pdf/2406.06769 Code/Web: allenai.github.io/discoveryworld Ai2 Microsoft Research

Only one month left to submit your papers to the AI & Scientific Discovery Workshop@NAACL 2025🥳

Call for papers: 🤖AI & Scientific Discovery 👩‍🔬 Workshop at NAACL 2025. Submissions due on 30th Jan 2025. 👩‍💻🧑‍💻

Only a few more days to submit your AI + Scientific Discovery papers to the AISD workshop NAACL HLT 2025! The cross-submission form is now active -- have a submitted or already-published paper and want to present it to scientific discovery colleagues? Submit today!

Thrilled to announce our work at CHI 2025 🥳 Kudos to Kevin Pu and all collaborators @siangliulue Tovi Grossman Kevin Feng Joseph Chee Chang Jonathan Bragg Matt Latzke Tom Hope Paper: arxiv.org/abs/2410.04025

We are excited to announce CodeScientist, a promising next step toward autonomous scientific discovery 🥳