Search Results for author: Gabriel Poesia

Found 9 papers, 6 papers with code

Hypothesis Search: Inductive Reasoning with Language Models

no code implementations11 Sep 2023 Ruocheng Wang, Eric Zelikman, Gabriel Poesia, Yewen Pu, Nick Haber, Noah D. Goodman

Because of the prohibitive cost of generation with state-of-the-art LLMs, we consider a middle step to filter the set of hypotheses that will be implemented into programs: we either ask the LLM to summarize into a smaller set of hypotheses, or ask human annotators to select a subset of the hypotheses.

In-Context Learning

Certified Deductive Reasoning with Language Models

no code implementations6 Jun 2023 Gabriel Poesia, Kanishk Gandhi, Eric Zelikman, Noah D. Goodman

In experiments on PrOntoQA, ProofWriter and Syllogism Validity datasets, \textsc{LogicGuide} significantly improves the performance of GPT-3, GPT-3. 5 Turbo and LLaMA (accuracy gains up to 35\%), while drastically reducing \emph{content effects} -- the interference between unwanted prior assumptions and reasoning, which humans and language models suffer from.

Logical Reasoning valid

Solving Math Word Problems by Combining Language Models With Symbolic Solvers

1 code implementation16 Apr 2023 Joy He-Yueya, Gabriel Poesia, Rose E. Wang, Noah D. Goodman

Automatically generating high-quality step-by-step solutions to math word problems has many applications in education.

GSM8K Language Modelling +1

Parsel: Algorithmic Reasoning with Language Models by Composing Decompositions

1 code implementation20 Dec 2022 Eric Zelikman, Qian Huang, Gabriel Poesia, Noah D. Goodman, Nick Haber

Despite recent success in large language model (LLM) reasoning, LLMs struggle with hierarchical multi-step reasoning tasks like generating complex programs.

Automated Theorem Proving Code Generation +4

Peano: Learning Formal Mathematical Reasoning

1 code implementation29 Nov 2022 Gabriel Poesia, Noah D. Goodman

We explore this idea in a case study on 5 sections of beginning algebra on the Khan Academy platform.

Automated Theorem Proving Mathematical Reasoning +1

Synchromesh: Reliable code generation from pre-trained language models

2 code implementations ICLR 2022 Gabriel Poesia, Oleksandr Polozov, Vu Le, Ashish Tiwari, Gustavo Soares, Christopher Meek, Sumit Gulwani

Then, Synchromesh feeds the examples to a pre-trained language model and samples programs using Constrained Semantic Decoding (CSD): a general framework for constraining the output to a set of valid programs in the target language.

Code Generation Language Modelling +1

Contrastive Reinforcement Learning of Symbolic Reasoning Domains

1 code implementation NeurIPS 2021 Gabriel Poesia, WenXin Dong, Noah Goodman

Our results suggest new directions for reinforcement learning in symbolic domains, as well as applications to mathematics education.

reinforcement-learning Reinforcement Learning (RL)

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