Akari Asai
@AkariAsai
Incoming Assistant Professor @SCSatCMU & research scientist @allen_ai akariasai @ 🦋
Some updates 🚨 I finished my Ph.D at @uwcse in June 2025! After a year at AI2 as a Research Scientist, I am joining CMU @LTIatCMU & @mldcmu (courtesy) as an Assistant Professor in Fall 2026. The journey, acknowledgments & recruiting in 🧵
The opportunity gap in AI is more striking than ever. We talk way too much about those receiving $100M or whatever for their jobs, but not enough those asking for <$1k to present their work. For 3rd year in a row, @ml_collective is raising funds to support @DeepIndaba attendees.
Today, I’m launching a deeply personal project. I’m betting $100M that we can help computer scientists create more upside impact for humanity. Built for and by researchers, including @JeffDean & @jpineau1 on the board, @LaudeInstitute catalyzes research with real-world impact.
Life update: I’m excited to share that I’ll be starting as faculty at the Max Planck Institute for Software Systems(@mpi_sws_) this Fall!🎉 I’ll be recruiting PhD students in the upcoming cycle, as well as research interns throughout the year: lasharavichander.github.io/contact.html
Congratulations and welcome!
Some updates 🚨 I finished my Ph.D at @uwcse in June 2025! After a year at AI2 as a Research Scientist, I am joining CMU @LTIatCMU & @mldcmu (courtesy) as an Assistant Professor in Fall 2026. The journey, acknowledgments & recruiting in 🧵
Going to #ICML2025 next week! Excited to chat about decentralized LM training, unified models, reasoning, and more. Please reach out if you like to meet up :)
The bottleneck in AI isn't just compute - it's access to diverse, high-quality data, much of which is locked away due to privacy, legal, or competitive concerns. What if there was a way to train better models collaboratively, without actually sharing your data? Introducing…
Introducing FlexOlmo, a new paradigm for language model training that enables the co-development of AI through data collaboration. 🧵
It has been great working on the project with support from @allen_ai! I believe there are many meaningful ways different people and orgs can work together to build strong shared models, and data collaboration might be the most impactful form of it. 📄Paper:…
Introducing FlexOlmo, a new paradigm for language model training that enables the co-development of AI through data collaboration. 🧵
Can data owners & LM developers collaborate to build a strong shared model while each retaining data control? Introducing FlexOlmo💪, a mixture-of-experts LM enabling: • Flexible training on your local data without sharing it • Flexible inference to opt in/out your data…
Introducing FlexOlmo, a new paradigm for language model training that enables the co-development of AI through data collaboration. 🧵
Worried about overfitting to IFEval? 🤔 Use ✨IFBench✨ our new, challenging instruction-following benchmark! Loved working w/ @valentina__py! Personal highlight: our multi-turn eval setting makes it possible to isolate constraint-following from the rest of the instruction 🔍
💡Beyond math/code, instruction following with verifiable constraints is suitable to be learned with RLVR. But the set of constraints and verifier functions is limited and most models overfit on IFEval. We introduce IFBench to measure model generalization to unseen constraints.
Deadline Extended! Submit to the LM4Sci Workshop @COLM_conf 2025 in Montreal 🧠 Large Language Modeling for Scientific Discovery (LM4Sci) 📅 New Deadline: June 30 📢 Notification: July 24 📍 Workshop: Oct 10, 2025 📝 Non-archival short (2–4p) & full (up to 8p) papers welcome!
A bit late to announce, but I’m excited to share that I'll be starting as an assistant professor at the University of Maryland @umdcs this August. I'll be recruiting PhD students this upcoming cycle for fall 2026. (And if you're a UMD grad student, sign up for my fall seminar!)
We’re organizing a workshop on LLMs for Scientific Discovery at #COLM2025 💡🧪🧬 Submit your exciting work by June 23! Stay tuned for our incredible speaker lineup!
🚨 Call for Papers: LM4Sci @COLM_conf 2025 🚨 Excited to announce the Large Language Modeling for Scientific Discovery (LM4Sci) workshop at COLM 2025 in Montreal, Canada! Submission Deadline: June 23 Notification: July 24 Workshop: October 10, 2025
LMs often output answers that sound right but aren’t supported by input context. This is intrinsic hallucination: the generation of plausible, but unsupported content. We propose Precise Information Control (PIC): a task requiring LMs to ground only on given verifiable claims.
Qwen3-0.6B x Wikipedia datastore is now supported in massive-serve! Serve a local API in one line: massive-serve serve --domain --domain_name dpr_wiki_qwen3_0.6b_ivfpq Use `dpr_wiki_qwen3_0.6b` for flat index. Examples of sending single/batch queries: github.com/RulinShao/mass…
🚀 Proud to introduce the Qwen3-Embedding and Qwen3-Reranker Series – setting new standards in multilingual text embedding and relevance ranking! ✨ Highlights: ✅ Available in 0.6B / 4B / 8B versions ✅ Supports 119 languages ✅ State-of-the-Art performance on MMTEB , MTEB ,…
We know Attention and its linear-time variants, such as linear attention and State Space Models. But what lies in between? Introducing Log-Linear Attention with: - Log-linear time training - Log-time inference (in both time and memory) - Hardware-efficient Triton kernels