Papers Mathematical Problem-Solving
“Mathematical Problem-Solving” 태그가 달린 논문 106편 · 필터 해제
Code-Vision: Evaluating Multimodal LLMs Logic Understanding and Code Generation Capabilities
This paper introduces Code-Vision, a benchmark designed to evaluate the logical understanding and code generation capabilities of Multimodal Large Language Models (MLLMs). It challenges MLLMs to generate a correct progra…
Code GenerationHumanEvalMathMathematical Problem-Solving+1MathFimer: Enhancing Mathematical Reasoning by Expanding Reasoning Steps through Fill-in-the-Middle Task
Mathematical reasoning represents a critical frontier in advancing large language models (LLMs). While step-by-step approaches have emerged as the dominant paradigm for mathematical problem-solving in LLMs, the quality o…
Code CompletionGSM8KMathMathematical Problem-Solving+1Teaching LLMs According to Their Aptitude: Adaptive Reasoning for Mathematical Problem Solving
Existing approaches to mathematical reasoning with large language models (LLMs) rely on Chain-of-Thought (CoT) for generalizability or Tool-Integrated Reasoning (TIR) for precise computation. While efforts have been made…
MathMathematical Problem-SolvingMathematical ReasoningSTRIVE: Structured Reasoning for Self-Improvement in Claim Verification
Claim verification is the task of determining whether a claim is supported or refuted by evidence. Self-improvement methods, where reasoning chains are generated and those leading to correct results are selected for trai…
Claim VerificationMathematical Problem-SolvingScaling Autonomous Agents via Automatic Reward Modeling And Planning
Large language models (LLMs) have demonstrated remarkable capabilities across a range of text-generation tasks. However, LLMs still struggle with problems requiring multi-step decision-making and environmental feedback, …
Decision MakingMathematical Problem-SolvingNavigateTask Planning+1Exposing Numeracy Gaps: A Benchmark to Evaluate Fundamental Numerical Abilities in Large Language Models
Large Language Models (LLMs) have demonstrated impressive capabilities in natural language processing tasks, such as text generation and semantic understanding. However, their performance on numerical reasoning tasks, su…
Language ModelingLanguage ModellingLogical ReasoningMathematical Problem-Solving+2Adaptive Graph of Thoughts: Test-Time Adaptive Reasoning Unifying Chain, Tree, and Graph Structures
Large Language Models (LLMs) have demonstrated impressive reasoning capabilities, yet their performance is highly dependent on the prompting strategy and model scale. While reinforcement learning and fine-tuning have bee…
Mathematical Problem-Solvingreinforcement-learningReinforcement LearningAdvancing Reasoning in Large Language Models: Promising Methods and Approaches
Large Language Models (LLMs) have succeeded remarkably in various natural language processing (NLP) tasks, yet their reasoning capabilities remain a fundamental challenge. While LLMs exhibit impressive fluency and factua…
Mathematical Problem-SolvingSurveyAutomating Mathematical Proof Generation Using Large Language Model Agents and Knowledge Graphs
Large Language Models have demonstrated remarkable capabilities in natural language processing tasks, including mathematical problem-solving that requires multi-step logical reasoning. However, challenges persist in auto…
Formal LogicKnowledge GraphsLanguage ModelingLanguage Modelling+5Token-Hungry, Yet Precise: DeepSeek R1 Highlights the Need for Multi-Step Reasoning Over Speed in MATH
This study investigates the performance of the DeepSeek R1 language model on 30 challenging mathematical problems derived from the MATH dataset, problems that previously proved unsolvable by other models under time const…
Language ModelingLanguage ModellingMathMathematical Problem-SolvingToken-by-Token Regeneration and Domain Biases: A Benchmark of LLMs on Advanced Mathematical Problem-Solving
Large language models (LLMs) excel in many natural language tasks, yet they struggle with complex mathemat-ical problem-solving, particularly in symbolic reasoning and maintaining consistent output. This study evalu-ates…
MathMathematical Problem-SolvingOpen Eyes, Then Reason: Fine-grained Visual Mathematical Understanding in MLLMs
Current multimodal large language models (MLLMs) often underperform on mathematical problem-solving tasks that require fine-grained visual understanding. The limitation is largely attributable to inadequate perception of…
MathMathematical Problem-SolvingMathematical ReasoningVisual GroundingVoxEval: Benchmarking the Knowledge Understanding Capabilities of End-to-End Spoken Language Models
With the rising need for speech-based interaction models, end-to-end Spoken Language Models (SLMs) have emerged as a promising solution. While these models require comprehensive world knowledge for meaningful and reliabl…
BenchmarkingMathematical Problem-SolvingMathematical ReasoningQuestion Answering+1Efficiently Serving LLM Reasoning Programs with Certaindex
The rapid evolution of large language models (LLMs) has unlocked their capabilities in advanced reasoning tasks like mathematical problem-solving, code generation, and legal analysis. Central to this progress are inferen…
Code GenerationMathematical Problem-SolvingSchedulingLarge Language Models for Mathematical Analysis
Mathematical problem-solving is a key field in artificial intelligence (AI) and a critical benchmark for evaluating the capabilities of large language models (LLMs). While extensive research has focused on mathematical p…
Mathematical Problem-SolvingMathematical ReasoningTraining and Evaluating Language Models with Template-based Data Generation
The rapid advancement of large language models (LLMs) such as GPT-3, PaLM, and Llama has significantly transformed natural language processing, showcasing remarkable capabilities in understanding and generating language.…
Data AugmentationMathMathematical Problem-SolvingMathematical ReasoningO1 Replication Journey -- Part 2: Surpassing O1-preview through Simple Distillation, Big Progress or Bitter Lesson?
This paper presents a critical examination of current approaches to replicating OpenAI's O1 model capabilities, with particular focus on the widespread but often undisclosed use of knowledge distillation techniques. Whil…
HallucinationKnowledge DistillationMathematical Problem-SolvingMathematical ReasoningKwai-STaR: Transform LLMs into State-Transition Reasoners
Mathematical reasoning presents a significant challenge to the cognitive capabilities of LLMs. Various methods have been proposed to enhance the mathematical ability of LLMs. However, few recognize the value of state tra…
GSM8KMathematical Problem-SolvingMathematical ReasoningHunyuan-Large: An Open-Source MoE Model with 52 Billion Activated Parameters by Tencent
In this paper, we introduce Hunyuan-Large, which is currently the largest open-source Transformer-based mixture of experts model, with a total of 389 billion parameters and 52 billion activation parameters, capable of ha…
Logical ReasoningMathematical Problem-SolvingMixture-of-ExpertsVisAidMath: Benchmarking Visual-Aided Mathematical Reasoning
Although previous research on large language models (LLMs) and large multi-modal models (LMMs) has systematically explored mathematical problem-solving (MPS) within visual contexts, the analysis of how these models proce…
BenchmarkingHallucinationMathematical Problem-SolvingMathematical Reasoning+1