Papers Math Word Problem Solving
“Math Word Problem Solving” 태그가 달린 논문 107편 · 필터 해제
A Diversity-Enhanced Knowledge Distillation Model for Practical Math Word Problem Solving
Math Word Problem (MWP) solving is a critical task in natural language processing, has garnered significant research interest in recent years. Various recent studies heavily rely on Seq2Seq models and their extensions (e…
DiversityKnowledge DistillationMathMath Word Problem SolvingLearning by Analogy: Enhancing Few-Shot Prompting for Math Word Problem Solving with Computational Graph-Based Retrieval
Large language models (LLMs) are known to struggle with complicated reasoning tasks such as math word problems (MWPs). In this paper, we present how analogy from similarly structured questions can improve LLMs' problem-s…
MathMath Word Problem SolvingRetrievalSBI-RAG: Enhancing Math Word Problem Solving for Students through Schema-Based Instruction and Retrieval-Augmented Generation
Many students struggle with math word problems (MWPs), often finding it difficult to identify key information and select the appropriate mathematical operations. Schema-based instruction (SBI) is an evidence-based strate…
GSM8KLanguage ModelingLanguage ModellingLarge Language Model+5When Not to Answer: Evaluating Prompts on GPT Models for Effective Abstention in Unanswerable Math Word Problems
Large language models (LLMs) are increasingly relied upon to solve complex mathematical word problems. However, being susceptible to hallucination, they may generate inaccurate results when presented with unanswerable qu…
HallucinationMathMath Word Problem SolvingTeaching-Inspired Integrated Prompting Framework: A Novel Approach for Enhancing Reasoning in Large Language Models
Large Language Models (LLMs) exhibit impressive performance across various domains but still struggle with arithmetic reasoning tasks. Recent work shows the effectiveness of prompt design methods in enhancing reasoning c…
Arithmetic ReasoningMathMathematical ReasoningMath Word Problem SolvingOpenMathInstruct-2: Accelerating AI for Math with Massive Open-Source Instruction Data
Mathematical reasoning continues to be a critical challenge in large language model (LLM) development with significant interest. However, most of the cutting-edge progress in mathematical reasoning with LLMs has become \…
Arithmetic ReasoningLarge Language ModelMathMathematical Reasoning+1Qwen2.5-Math Technical Report: Toward Mathematical Expert Model via Self-Improvement
In this report, we present a series of math-specific large language models: Qwen2.5-Math and Qwen2.5-Math-Instruct-1.5B/7B/72B. The core innovation of the Qwen2.5 series lies in integrating the philosophy of self-improve…
GSM8KMathMathematical ReasoningMath Word Problem Solving+1Qwen2 Technical Report
This report introduces the Qwen2 series, the latest addition to our large language models and large multimodal models. We release a comprehensive suite of foundational and instruction-tuned language models, encompassing …
Arithmetic ReasoningGSM8KHumanEvalLanguage Modelling+4Step-DPO: Step-wise Preference Optimization for Long-chain Reasoning of LLMs
Mathematical reasoning presents a significant challenge for Large Language Models (LLMs) due to the extensive and precise chain of reasoning required for accuracy. Ensuring the correctness of each reasoning step is criti…
Arithmetic ReasoningGSM8KMathMathematical Reasoning+1DART-Math: Difficulty-Aware Rejection Tuning for Mathematical Problem-Solving
Solving mathematical problems requires advanced reasoning abilities and presents notable challenges for large language models. Previous works usually synthesize data from proprietary models to augment existing datasets, …
Arithmetic ReasoningMathMathematical Problem-SolvingMath Word Problem Solving+1Program Synthesis Benchmark for Visual Programming in XLogoOnline Environment
Large language and multimodal models have shown remarkable successes on various benchmarks focused on specific skills such as general-purpose programming, natural language understanding, math word problem-solving, and vi…
Logical ReasoningMathMath Word Problem SolvingNatural Language Understanding+3AlphaMath Almost Zero: Process Supervision without Process
Although recent advancements in large language models (LLMs) have significantly improved their performance on various tasks, they still face challenges with complex and symbolic multi-step reasoning, particularly in math…
Mathematical ReasoningMath Word Problem SolvingAchieving >97% on GSM8K: Deeply Understanding the Problems Makes LLMs Better Solvers for Math Word Problems
Chain-of-Thought (CoT) prompting has enhanced the performance of Large Language Models (LLMs) across various reasoning tasks. However, CoT still falls short in dealing with complex math word problems, as it usually suffe…
Arithmetic ReasoningGSM8KMathMath Word Problem SolvingToward Self-Improvement of LLMs via Imagination, Searching, and Criticizing
Despite the impressive capabilities of Large Language Models (LLMs) on various tasks, they still struggle with scenarios that involves complex reasoning and planning. Recent work proposed advanced prompting techniques an…
Arithmetic ReasoningGSM8KMathMathematical Reasoning+2MACM: Utilizing a Multi-Agent System for Condition Mining in Solving Complex Mathematical Problems
Recent advancements in large language models, such as GPT-4, have demonstrated remarkable capabilities in processing standard queries. Despite these advancements, their performance substantially declines in \textbf{advan…
Logical ReasoningMathMath Word Problem SolvingData Augmentation with In-Context Learning and Comparative Evaluation in Math Word Problem Solving
Math Word Problem (MWP) solving presents a challenging task in Natural Language Processing (NLP). This study aims to provide MWP solvers with a more diverse training set, ultimately improving their ability to solve vario…
Data AugmentationIn-Context LearningLanguage ModelingLanguage Modelling+2Branch-Train-MiX: Mixing Expert LLMs into a Mixture-of-Experts LLM
We investigate efficient methods for training Large Language Models (LLMs) to possess capabilities in multiple specialized domains, such as coding, math reasoning and world knowledge. Our method, named Branch-Train-MiX (…
Arithmetic ReasoningCode GenerationCommon Sense ReasoningMath+5Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context
In this report, we introduce the Gemini 1.5 family of models, representing the next generation of highly compute-efficient multimodal models capable of recalling and reasoning over fine-grained information from millions …
1 Image, 2*2 StitchingCode GenerationFS-MEVQAImage Retrieval+8Key-Point-Driven Data Synthesis with its Enhancement on Mathematical Reasoning
Large language models (LLMs) have shown great potential in complex reasoning tasks, yet their performance is often hampered by the scarcity of high-quality and reasoning-focused training datasets. Addressing this challen…
GSM8KMathMathematical ReasoningMath Word Problem SolvingGSM-Plus: A Comprehensive Benchmark for Evaluating the Robustness of LLMs as Mathematical Problem Solvers
Large language models (LLMs) have achieved impressive performance across various mathematical reasoning benchmarks. However, there are increasing debates regarding whether these models truly understand and apply mathemat…
GSM8KMathMathematical ReasoningMath Word Problem Solving