Hypothesis Search: Inductive Reasoning with Language Models

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Wang, Ruocheng, Zelikman, Eric, Poesia, Gabriel, Pu, Yewen, Haber, Nick, Goodman, Noah D.
Format:	Preprint
Published:	2023
Subjects:	Machine Learning Artificial Intelligence Computation and Language
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Quiet-STaR: Language Models Can Teach Themselves to Think Before Speaking
by: Zelikman, Eric, et al.
Published: (2024)

From Next-Token to Mathematics: The Learning Dynamics of Mathematical Reasoning in Language Models
by: Mishra, Shubhra, et al.
Published: (2024)

Large Language Model Reasoning Failures
by: Song, Peiyang, et al.
Published: (2026)

Stream of Search (SoS): Learning to Search in Language
by: Gandhi, Kanishk, et al.
Published: (2024)

Hypothesis Generation and Inductive Inference in Children and Language Models
by: Qin, Jeffrey, et al.
Published: (2026)

Learning Formal Mathematics From Intrinsic Motivation
by: Poesia, Gabriel, et al.
Published: (2024)

Self-Taught Optimizer (STOP): Recursively Self-Improving Code Generation
by: Zelikman, Eric, et al.
Published: (2023)

Generating Pragmatic Examples to Train Neural Program Synthesizers
by: Vaduguru, Saujas, et al.
Published: (2023)

Is Child-Directed Speech Effective Training Data for Language Models?
by: Feng, Steven Y., et al.
Published: (2024)

The Role of Deductive and Inductive Reasoning in Large Language Models
by: Cai, Chengkun, et al.
Published: (2024)

CriticAL: Critic Automation with Language Models
by: Li, Michael Y., et al.
Published: (2024)

ORION: Teaching Language Models to Reason Efficiently in the Language of Thought
by: Tanmay, Kumar, et al.
Published: (2025)

On the Inductive Bias of Stacking Towards Improving Reasoning
by: Saunshi, Nikunj, et al.
Published: (2024)

Language and Experience: A Computational Model of Social Learning in Complex Tasks
by: Colas, Cédric, et al.
Published: (2025)

Mars: Situated Inductive Reasoning in an Open-World Environment
by: Tang, Xiaojuan, et al.
Published: (2024)

Symmetrical Visual Contrastive Optimization: Aligning Vision-Language Models with Minimal Contrastive Images
by: Wu, Shengguang, et al.
Published: (2025)

Read and Reap the Rewards: Learning to Play Atari with the Help of Instruction Manuals
by: Wu, Yue, et al.
Published: (2023)

The Linear Representation Hypothesis and the Geometry of Large Language Models
by: Park, Kiho, et al.
Published: (2023)

CodeARC: Benchmarking Reasoning Capabilities of LLM Agents for Inductive Program Synthesis
by: Wei, Anjiang, et al.
Published: (2025)

The Consistency Hypothesis in Uncertainty Quantification for Large Language Models
by: Xiao, Quan, et al.
Published: (2025)

Belief Dynamics Reveal the Dual Nature of In-Context Learning and Activation Steering
by: Bigelow, Eric, et al.
Published: (2025)

Think Before You Prune: Self-Reflective Structured Pruning for Reasoning Language Models
by: Wang, Ziyan, et al.
Published: (2025)

SealQA: Raising the Bar for Reasoning in Search-Augmented Language Models
by: Pham, Thinh, et al.
Published: (2025)

Program Synthesis using Inductive Logic Programming for the Abstraction and Reasoning Corpus
by: Rocha, Filipe Marinho, et al.
Published: (2024)

Combining Induction and Transduction for Abstract Reasoning
by: Li, Wen-Ding, et al.
Published: (2024)

Big-Math: A Large-Scale, High-Quality Math Dataset for Reinforcement Learning in Language Models
by: Albalak, Alon, et al.
Published: (2025)

Hypothesis Generation with Large Language Models
by: Zhou, Yangqiaoyu, et al.
Published: (2024)

Variational Reasoning for Language Models
by: Zhou, Xiangxin, et al.
Published: (2025)

When Do Skills Help Reinforcement Learning? A Theoretical Analysis of Temporal Abstractions
by: Li, Zhening, et al.
Published: (2024)

EvoLM: In Search of Lost Language Model Training Dynamics
by: Qi, Zhenting, et al.
Published: (2025)

Data-Driven Calibration of Prediction Sets in Large Vision-Language Models Based on Inductive Conformal Prediction
by: Ye, Yuanchang, et al.
Published: (2025)

Phenomenal Yet Puzzling: Testing Inductive Reasoning Capabilities of Language Models with Hypothesis Refinement
by: Qiu, Linlu, et al.
Published: (2023)

A Reply to Makelov et al. (2023)'s "Interpretability Illusion" Arguments
by: Wu, Zhengxuan, et al.
Published: (2024)

Sequences of Logits Reveal the Low Rank Structure of Language Models
by: Golowich, Noah, et al.
Published: (2025)

SILO Language Models: Isolating Legal Risk In a Nonparametric Datastore
by: Min, Sewon, et al.
Published: (2023)

Compositional Reasoning with Transformers, RNNs, and Chain of Thought
by: Yehudai, Gilad, et al.
Published: (2025)

Inductive Biases for Zero-shot Systematic Generalization in Language-informed Reinforcement Learning
by: Dijujin, Negin Hashemi, et al.
Published: (2025)

Guiding Language Model Reasoning with Planning Tokens
by: Wang, Xinyi, et al.
Published: (2023)

Towards Reasoning Ability of Small Language Models
by: Srivastava, Gaurav, et al.
Published: (2025)

Understanding Reasoning Ability of Language Models From the Perspective of Reasoning Paths Aggregation
by: Wang, Xinyi, et al.
Published: (2024)