https://github.com/neurasearch/neurips-2022-submission-3358
공식 코드ELASTIC: Numerical Reasoning with Adaptive Symbolic Compiler
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
A math word problem is a mathematical exercise (such as in a textbook, worksheet, or exam) where significant background information on the problem is presented in ordinary language rather than in mathematical notation. As most word problems involve a narrative of some sort, they are sometimes referred to as story problems and may vary in the amount of technical language used.
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
ELASTIC: Numerical Reasoning with Adaptive Symbolic Compiler
MuggleMath: Assessing the Impact of Query and Response Augmentation on Math Reasoning
Recall and Learn: A Memory-augmented Solver for Math Word Problems
Math Word Problem Solving by Generating Linguistic Variants of Problem Statements
RetICL: Sequential Retrieval of In-Context Examples with Reinforcement Learning
VerityMath: Advancing Mathematical Reasoning by Self-Verification Through Unit Consistency
Automatic Model Selection with Large Language Models for Reasoning
FinanceMath: Knowledge-Intensive Math Reasoning in Finance Domains
LogicSolver: Towards Interpretable Math Word Problem Solving with Logical Prompt-enhanced Learning
Toward Self-Improvement of LLMs via Imagination, Searching, and Criticizing
MathChat: Converse to Tackle Challenging Math Problems with LLM Agents
Reverse Operation based Data Augmentation for Solving Math Word Problems
Multi-View Reasoning: Consistent Contrastive Learning for Math Word Problem
LogicSolver: Towards Interpretable Math Word Problem Solving with Logical Prompt-enhanced Learning
Ape210K: A Large-Scale and Template-Rich Dataset of Math Word Problems
Branch-Train-MiX: Mixing Expert LLMs into a Mixture-of-Experts LLM
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.