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Dylan Foster 🐢

Dylan Foster 🐢

Bluesky @djfoster.bsky.social
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🔄 Data last refreshed 16 days ago
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Make a deal with Dylan Foster 🐢

🔒 Paid proposals held safely in escrow — released only when the work's approved.

📣Sponsored postOne post with your link and message, clearly disclosed. $20→ 🧵Sponsored threadA 3–5 post storytelling thread — Bluesky rewards substance o… $50→ 📌Pinned sponsored postA sponsored post pinned to the top of my profile for the mon… $60/mo→ 🔗Link-in-bio placementYour link in my bio for the month. $30/mo→ 🔁Repost packageI repost your account's posts through the month — distributi… $40/mo→ ⭐Starter-pack placementYour account included in my starter pack — new users follow … $40/mo→ 🎁Giveaway postYou supply the prize — I run the giveaway post and pick winn… $16→ 📦Product seeding / honest reviewSend me your product — I post a disclosed, honest take. Auth… $24→ 🤝Mutual shoutout collabWe shout each other out — a value swap between accounts. Swap→ 🎬UGC HireBranded content for your own channels & ads from $50→ 🎙️Podcast guest spotInvite Dylan Foster 🐢 onto your podcast (~45 min, remote) $32→

Every booking is a normal escrow-protected deal.

Followers
2.5K
Account age
1 yrs
🧰 Free analysis for Dylan Foster 🐢
🕵️ Fake follower check 📊 Engagement rate 💰 What they charge

Known for

Reinforcement learning has led to amazing breakthroughs in reasoning (e.g., R1), but can it discover truly new behaviors not already present in the base model? A new paper with Zak Mhammedi and Dhruv Rohatgi: The Computational Role of the Base Model in Exploration arxiv.org/abs/2503.0745356 views Reinforcement learning has led to amazing breakthroughs in reasoning (e.g., R1), but can it discover truly new behaviors not already present in the base model? A new paper with Zak Mhammedi and Dhruv Rohatgi: The Computational Role of the Base Model in Exploration arxiv.org/abs/2503.07453 Is Best-of-N really the best we can do for language model inference? New paper (appearing at ICML) led by the amazing Audrey Huang (ahahaudrey.bsky.social) with Adam Block, Qinghua Liu, Nan Jiang, and Akshay Krishnamurthy (akshaykr.bsky.social). 1/1126 views Is Best-of-N really the best we can do for language model inference? New paper (appearing at ICML) led by the amazing Audrey Huang (ahahaudrey.bsky.social) with Adam Block, Qinghua Liu, Nan Jiang, and Akshay Krishnamurthy (akshaykr.bsky.social). 1/11 Announcing the first workshop on Foundations of Post-Training (FoPT) at COLT 2025! 📝 Soliciting abstracts/posters exploring theoretical & practical aspects of post-training and RL with language models! 🗓️ Deadline: May 19, 202521 views Announcing the first workshop on Foundations of Post-Training (FoPT) at COLT 2025! 📝 Soliciting abstracts/posters exploring theoretical & practical aspects of post-training and RL with language models! 🗓️ Deadline: May 19, 2025 The coverage principle: How pre-training enables post-training New preprint where we look at the mechanisms through which next-token prediction produces models that succeed at downstream tasks. The answer involves a metric we call the "coverage profile", not cross-entropy.19 views The coverage principle: How pre-training enables post-training New preprint where we look at the mechanisms through which next-token prediction produces models that succeed at downstream tasks. The answer involves a metric we call the "coverage profile", not cross-entropy.

📊 Post engagement

18
Avg engagement / post
0.7%
Engagement vs followers
Nov 2024
On Bluesky since

🔥 Top post: Reinforcement learning has led to amazing breakthroughs in reaso · 56 likes + reposts

📊 Activity & format

Posting cadence
0.4 / week
A lower-frequency account — each post lands with more weight.
Content mix
Mostly images
Recent: 4 text · 8 image · 0 video.

Recent posts

View on Bluesky ↗
🔥 Top post Reinforcement learning has led to amazing breakthroughs in reasoning (e.g., R1), but can it discover truly new behaviors not already present in the base model? A new paper with Zak Mhammedi and Dhruv Rohatgi: The Computational Role of the Base Model in Exploration arxiv.org/a… ★ 56
The coverage principle: How pre-training enables post-training New preprint where we look at the mechanisms through which next-token prediction produces models that succeed at downstream tasks. The answer involves a metric we call the "… ★ 19 Taming Imperfect Process Verifiers: A Sampling Perspective on Backtracking. A totally new framework based on ~backtracking~ for using process verifiers to guide inference, w/ connections to approximate counting/sampling in theoretical CS.… ★ 3 MSR NYC is hiring spring and summer interns in AI/ML/RL! Apply here: jobs.careers.microsoft.com/global/en/jo... ★ 27 Microsoft Research New York City (www.microsoft.com/en-us/resear...) is seeking applicants for multiple Postdoctoral Researcher positions in ML/AI! These are positions for up to 2 years, starting in July 2026. Application deadline: Octo… ★ 12 Quick reminder: The deadline for our workshop on Foundations of Reasoning in Language Models (FoRLM) at NeurIPS 2025 is next Wednesday, Sept 3! Announcing the first workshop on Foundations of Language Model Reasoning (FoRLM) at NeurIPS 2025! 📝Soliciting abstracts that advance foundational understanding of reasoning in language models, from theoretical analyses to rigorous empiric… ★ 13 For those at ICML, Audrey will be presenting this paper at the 4:30pm poster session this afternoon! West Exhibition Hall B2-B3 W-1009 ★ 3 Dhruv Rohatgi will be giving a lecture on our recent work on comp-stat tradeoffs in next-token prediction at the RL Theory virtual seminar series (rl-theory.bsky.social) tomorrow at 2pm EST! Should be a fun talk---come check it out!! ★ 15 The abstract submission deadline for FoPt has been extended to the 21st of May (11:59pm UTC). Submission website: openreview.net/group?id=lea... ★ 5 Announcing the first workshop on Foundations of Post-Training (FoPT) at COLT 2025! 📝 Soliciting abstracts/posters exploring theoretical & practical aspects of post-training and RL with language models! 🗓️ Deadline: May 19, 2025 ★ 21 Is Best-of-N really the best we can do for language model inference? New paper (appearing at ICML) led by the amazing Audrey Huang (ahahaudrey.bsky.social) with Adam Block, Qinghua Liu, Nan Jiang, and Akshay Krishnamurthy (akshaykr.bsky.s… ★ 26

🦋 Handle & authenticity

Bluesky handle
@djfoster.bsky.social
A default .bsky.social handle — genuine, but not domain-verified. Confirm identity before a high-value deal.
On Bluesky since
Nov 2024
Joined after Bluesky opened to the public — a settled account with a real history.

💡 Facts

🗓️Joined Bluesky in 2024 — 1 year ago.
👁️Averages 18 views per post.
📤Posts about 0.4× per week.

🕵️ Fake follower check

Estimated
59/100
Fair Credibility score
84%
Real Real audience
Low Fake-follower risk
Medium Data confidence
  • Est. 84% real, active audience · Low fake-follower risk.
  • Engagement (~0.7% of followers engage each post) is around typical for Bluesky.

Heuristic estimate from engagement, follower ratios, account age & growth — a screening signal, not a guarantee.

About

Principal Researcher in AI/ML/RL Theory @ Microsoft Research NE/NYC. Previously @ MIT, Cornell. http://dylanfoster.net RL Theory Lecture Notes: https://arxiv.org/abs/2312.16730

📸 Gallery

The coverage principle: How pre-training enables post-training New preprint where we look at the mechanisms through which next-token prediction produces models that succeed at downstream tasks. The answer involves a metric we call the "coverage profile", not cross-entropy. Taming Imperfect Process Verifiers: A Sampling Perspective on Backtracking. A totally new framework based on ~backtracking~ for using process verifiers to guide inference, w/ connections to approximate counting/sampling in theoretical CS. Paper: www.arxiv.org/abs/2510.03149 Announcing the first workshop on Foundations of Language Model Reasoning (FoRLM) at NeurIPS 2025! 📝Soliciting abstracts that advance foundational understanding of reasoning in language models, from theoretical analyses to rigorous empirical studies. 📆 Deadline: Sept 3, 2025 For those at ICML, Audrey will be presenting this paper at the 4:30pm poster session this afternoon! West Exhibition Hall B2-B3 W-1009 Dhruv Rohatgi will be giving a lecture on our recent work on comp-stat tradeoffs in next-token prediction at the RL Theory virtual seminar series (rl-theory.bsky.social) tomorrow at 2pm EST! Should be a fun talk---come check it out!! Announcing the first workshop on Foundations of Post-Training (FoPT) at COLT 2025! 📝 Soliciting abstracts/posters exploring theoretical & practical aspects of post-training and RL with language models! 🗓️ Deadline: May 19, 2025 Is Best-of-N really the best we can do for language model inference? New paper (appearing at ICML) led by the amazing Audrey Huang (ahahaudrey.bsky.social) with Adam Block, Qinghua Liu, Nan Jiang, and Akshay Krishnamurthy (akshaykr.bsky.social). 1/11 Reinforcement learning has led to amazing breakthroughs in reasoning (e.g., R1), but can it discover truly new behaviors not already present in the base model? A new paper with Zak Mhammedi and Dhruv Rohatgi: The Computational Role of the Base Model in Exploration arxiv.org/abs/2503.07453

🔀 Audience overlap

Estimated

Estimated shared audience with similar creators — useful for avoiding overlap (or doubling down) when planning a campaign.

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