AI People Wiki

Builders & open source

Valentina Pyatkin

Researcher working on LLM post-training for the Swiss AI Initiative, ETH AI Center

  • Researcher working on LLM post-training for the Swiss AI Initiative, ETH AI Center1

Valentina Pyatkin is a researcher at the ETH AI Center, working on post-training of large language models for the Swiss AI Initiative and contributing to Apertus. Pyatkin was previously a postdoctoral researcher at the Allen Institute for AI (Ai2) and the University of Washington, where Pyatkin worked on open post-training efforts including Tülu 3 and contributed to OLMo. Pyatkin is the third author of the Tülu 3 report and has built benchmarks such as RewardBench and IFBench.12

At a glance

Current role
Researcher working on LLM post-training for the Swiss AI Initiative
Sector
University
Education
UW
Work listed
2
Honors
4
Sources cited
3
Profile reviewed

Career

Pyatkin completed a PhD in computer science at the NLP lab of Bar-Ilan University, supervised by Ido Dagan and Reut Tsarfaty, and interned twice at Ai2. Pyatkin then held a postdoctoral position at Ai2 and the University of Washington, advised by Hannaneh Hajishirzi and Yejin Choi.1

Pyatkin is now a researcher at the ETH AI Center, working on post-training of language models for the Swiss AI Initiative and contributing to the Apertus models.1

Research

Pyatkin's research centres on post-training and adaptation of language models, including how models follow instructions and constraints and how preference and reward signals shape their behaviour. At Ai2, Pyatkin worked on the Tülu post-training pipelines, which combine supervised finetuning, direct preference optimization and reinforcement learning with verifiable rewards, and contributed to OLMo and OLMo 2.12

Pyatkin has also built evaluation benchmarks, including RewardBench and IFBench, and co-authored RewardBench 2, published at ICLR 2026.1

Work and contributions

  • Llama 3.1 Tülu 3.1 8B Open weights

    Third author of the Tülu 3 post-training report, which the Tülu 3.1 8B model card cites as its paper; Pyatkin describes being a core contributor to the Tülu and Open-Instruct project.231

  • IF-RLVR: Generalizing Verifiable Instruction Following Published research

    First author of a NeurIPS 2025 paper on generalizing verifiable instruction following, with co-authors including Pradeep Dasigi and Nathan Lambert.1

Timeline

  1. Received the AI2 Outstanding Intern of the Year Award.1
  2. Received the ACL Best Theme Paper Award for OLMo and an ACL Outstanding Paper Award.1
  3. Co-authored the Tülu 3 report on open language model post-training as third author.2
  4. Had the IFBench paper accepted to NeurIPS 2025.1
  5. Co-authored RewardBench 2, published at ICLR 2026.1

Other documented roles

Roles the sources document that are not confirmed as current.

Honors and recognition

  • AI2 Outstanding Intern of the Year Award · Allen Institute for AI, 20231
  • DAAD AInet Fellow · German Academic Exchange Service (DAAD), 20231
  • ACL Best Theme Paper Award (for OLMo) · Association for Computational Linguistics, 20241
  • ACL Outstanding Paper Award · Association for Computational Linguistics, 20241

Where they work

Suggest a correction or removal

Profiles cover public professional work only, and each statement cites a source. If something is out of date, missing or wrong, tell us and link a source. People can also ask for their profile to be corrected or removed.

References

3 sources · profile reviewed Oct 22, 2026 · data updated Oct 22, 2026

  1. Valentina Pyatkin — homepageValentina Pyatkin · Official page · accessed Oct 22, 2026
  2. Tulu 3: Pushing Frontiers in Open Language Model Post-Training (arXiv 2411.15124)arXiv · Paper · published Nov 22, 2024 · accessed Oct 22, 2026
  3. allenai/Llama-3.1-Tulu-3.1-8B model cardAi2 (Hugging Face) · Model card · accessed Oct 22, 2026