Jesse Mu Profile picture
Nov 21 8 tweets 6 min read
Excited to present 3 #NeurIPS2022 papers on a trend I've been very excited about recently: blurring the boundaries between language models and RL agents

(+a bonus 4th paper on active learning!)

🧵(0/7)

PS: I'm on the industry job market! The "They're the same picture" The Office meme. Th
1️⃣ Improving Intrinsic Exploration with Language Abstractions

Using language abstractions to guide exploration in RL, e.g. by self-designing a curriculum of increasingly difficult language goals



Also see @ykilcher review:

(1/7)
2️⃣ Improving Policy Learning with Language Dynamics Distillation (led by @hllo_wrld)

Increasing RL sample efficiency by pretraining agents to model env dynamics from language-annotated demonstrations



(2/7)
3️⃣ STaR: Bootstrapping Reasoning with Reasoning (led by @ericzelikman, @Yuhu_ai_)

Improving multistep reasoning in LMs by bootstrapping off of self-generated rationales

Essentially doing RL in chain-of-thought rationale space!



(3/7)
4️⃣ (bonus!) Active Learning Helps Pretrained Models Learn the Intended Task (led by @AlexTamkin)

Revisiting classic active learning techniques in the context of modern foundation models and few-shot task ambiguity



(4/7)
To recap, I see LMs and RL converging from 2 directions:

RL➡️?⬅️LMs

Starting from RL: imbuing agents w/ language priors [1️⃣,2️⃣]
Starting from LMs: improving reasoning not from static corpora, but RL exploration & interaction [3️⃣]

Excited for these paths to intertwine!

(5/7)
I'm on the job market! Mostly industry (+startups). Interested in both traditional RS positions *and* applied roles deploying products to users and improving from feedback. Please DM or reach out at NeurIPS!

(Also reach out in general, happy to chat about anything)

(6/7)
Thank you to my wonderful coauthors: @robertarail, @hllo_wrld, @MinqiJiang, @_rockt, @egrefen, @LukeZettlemoyer, @ericzelikman, @Yuhu_ai_, @AlexTamkin, Salil Deshpande, Dat Nguyen, and Noah Goodman!

(7/7)

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