Papers Mathematical Problem-Solving
“Mathematical Problem-Solving” 태그가 달린 논문 106편 · 필터 해제
Agent RL Scaling Law: Agent RL with Spontaneous Code Execution for Mathematical Problem Solving
Large Language Models (LLMs) often struggle with mathematical reasoning tasks requiring precise, verifiable computation. While Reinforcement Learning (RL) from outcome-based rewards enhances text-based reasoning, underst…
MathMathematical Problem-SolvingMathematical ReasoningReinforcement Learning (RL)Reasoning Models Can Be Effective Without Thinking
Recent LLMs have significantly improved reasoning capabilities, primarily by including an explicit, lengthy Thinking process as part of generation. In this paper, we question whether this explicit thinking is necessary. …
Automated Theorem ProvingMathematical Problem-SolvingHolistic Capability Preservation: Towards Compact Yet Comprehensive Reasoning Models
This technical report presents Ring-Lite-Distill, a lightweight reasoning model derived from our open-source Mixture-of-Experts (MoE) Large Language Models (LLMs) Ling-Lite. This study demonstrates that through meticulou…
Instruction FollowingMathematical Problem-SolvingMixture-of-ExpertsOn Vanishing Variance in Transformer Length Generalization
It is a widely known issue that Transformers, when trained on shorter sequences, fail to generalize robustly to longer ones at test time. This raises the question of whether Transformer models are real reasoning engines,…
AttributeMathematical Problem-SolvingLearNAT: Learning NL2SQL with AST-guided Task Decomposition for Large Language Models
Natural Language to SQL (NL2SQL) has emerged as a critical task for enabling seamless interaction with databases. Recent advancements in Large Language Models (LLMs) have demonstrated remarkable performance in this domai…
Mathematical Problem-SolvingPrompt Engineeringreinforcement-learningReinforcement LearningExploring LLM Reasoning Through Controlled Prompt Variations
This study investigates the reasoning robustness of large language models (LLMs) on mathematical problem-solving tasks under systematically introduced input perturbations. Using the GSM8K dataset as a controlled testbed,…
GSM8KMathematical Problem-SolvingBrains vs. Bytes: Evaluating LLM Proficiency in Olympiad Mathematics
Recent advancements in large language models (LLMs) have shown impressive progress in mathematical reasoning tasks. However, current evaluation benchmarks predominantly focus on the accuracy of final answers, often overl…
MathMathematical Problem-SolvingMathematical ReasoningEntropy-Based Adaptive Weighting for Self-Training
The mathematical problem-solving capabilities of large language models have become a focal point of research, with growing interests in leveraging self-generated reasoning paths as a promising way to refine and enhance t…
GSM8KMathMathematical Problem-SolvingMathAgent: Leveraging a Mixture-of-Math-Agent Framework for Real-World Multimodal Mathematical Error Detection
Mathematical error detection in educational settings presents a significant challenge for Multimodal Large Language Models (MLLMs), requiring a sophisticated understanding of both visual and textual mathematical content …
MathMathematical Problem-SolvingA Survey on Mathematical Reasoning and Optimization with Large Language Models
Mathematical reasoning and optimization are fundamental to artificial intelligence and computational problem-solving. Recent advancements in Large Language Models (LLMs) have significantly improved AI-driven mathematical…
Automated Theorem ProvingHeuristic SearchMathematical Problem-SolvingMathematical Reasoning+2Does Chain-of-Thought Reasoning Help Mobile GUI Agent? An Empirical Study
Reasoning capabilities have significantly improved the performance of vision-language models (VLMs) in domains such as mathematical problem-solving, coding, and visual question-answering. However, their impact on real-wo…
AttributeMathematical Problem-SolvingQuestion AnsweringVisual Question AnsweringMathFusion: Enhancing Mathematic Problem-solving of LLM through Instruction Fusion
Large Language Models (LLMs) have shown impressive progress in mathematical reasoning. While data augmentation is promising to enhance mathematical problem-solving ability, current approaches are predominantly limited to…
Data AugmentationMathematical Problem-SolvingMathematical ReasoningMathFlow: Enhancing the Perceptual Flow of MLLMs for Visual Mathematical Problems
Despite impressive performance across diverse tasks, Multimodal Large Language Models (MLLMs) have yet to fully demonstrate their potential in visual mathematical problem-solving, particularly in accurately perceiving an…
Mathematical Problem-SolvingPerformance Comparison of Large Language Models on Advanced Calculus Problems
This paper presents an in-depth analysis of the performance of seven different Large Language Models (LLMs) in solving a diverse set of math advanced calculus problems. The study aims to evaluate these models' accuracy, …
MathMathematical Problem-SolvingSelf-Evolved Preference Optimization for Enhancing Mathematical Reasoning in Small Language Models
Large language models (LLMs) have significantly improved their reasoning capabilities; however, they still struggle with complex multi-step mathematical problem-solving due to error propagation, lack of self-correction, …
GSM8KMathMathematical Problem-SolvingMathematical Reasoning+1Nexus: A Lightweight and Scalable Multi-Agent Framework for Complex Tasks Automation
Recent advancements in Large Language Models (LLMs) have substantially evolved Multi-Agent Systems (MASs) capabilities, enabling systems that not only automate tasks but also leverage near-human reasoning capabilities. T…
Code GenerationHumanEvalLogical ReasoningMath+1SECURA: Sigmoid-Enhanced CUR Decomposition with Uninterrupted Retention and Low-Rank Adaptation in Large Language Models
With the rapid development of large language models (LLMs), fully fine-tuning (FT) these models has become increasingly impractical due to the high computational demands. Additionally, FT can lead to catastrophic forgett…
Continual LearningGSM8KMathematical Problem-SolvingMultiple-choice+2How Do Large Language Monkeys Get Their Power (Laws)?
Recent research across mathematical problem solving, proof assistant programming and multimodal jailbreaking documents a striking finding: when (multimodal) language model tackle a suite of tasks with multiple attempts p…
Language ModelingLanguage ModellingMathematical Problem-SolvingForgotten Polygons: Multimodal Large Language Models are Shape-Blind
Despite strong performance on vision-language tasks, Multimodal Large Language Models (MLLMs) struggle with mathematical problem-solving, with both open-source and state-of-the-art models falling short of human performan…
MathMathematical Problem-SolvingMathematical ReasoningVisual ReasoningNavigating Semantic Relations: Challenges for Language Models in Abstract Common-Sense Reasoning
Large language models (LLMs) have achieved remarkable performance in generating human-like text and solving reasoning tasks of moderate complexity, such as question-answering and mathematical problem-solving. However, th…
Common Sense ReasoningMathematical Problem-SolvingPrompt EngineeringQuestion Answering