Papers Math
“Math” 태그가 달린 논문 1,596편 · 필터 해제
Enigmata: Scaling Logical Reasoning in Large Language Models with Synthetic Verifiable Puzzles
Large Language Models (LLMs), such as OpenAI's o1 and DeepSeek's R1, excel at advanced reasoning tasks like math and coding via Reinforcement Learning with Verifiable Rewards (RLVR), but still struggle with puzzles solva…
ARCLogical ReasoningMathMathematical ReasoningInference-time Alignment in Continuous Space
Aligning large language models with human feedback at inference time has received increasing attention due to its flexibility. Existing methods rely on generating multiple responses from the base policy for search using …
MathPrismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning
Effective generalization in language models depends critically on the diversity of their training data. Yet existing diversity metrics often fall short of this goal, relying on surface-level heuristics that are decoupled…
DiversityMathNatural Language InferenceWhich Data Attributes Stimulate Math and Code Reasoning? An Investigation via Influence Functions
Large language models (LLMs) have demonstrated remarkable reasoning capabilities in math and coding, often bolstered by post-training on the chain-of-thoughts (CoTs) generated by stronger models. However, existing strate…
AttributeMathDone Is Better than Perfect: Unlocking Efficient Reasoning by Structured Multi-Turn Decomposition
Large Reasoning Models (LRMs) are criticized for the excessively lengthy Chain-of-Thought (CoT) to derive the final answer, suffering from high first-token and overall latency. Typically, the CoT of LRMs mixes multiple t…
MathReinforcement Learning (RL)Unifying Multimodal Large Language Model Capabilities and Modalities via Model Merging
While foundation models update slowly due to resource-intensive training requirements, domain-specific models evolve between updates. Model merging aims to combine multiple expert models into a single, more capable model…
Language ModelingLanguage ModellingLarge Language ModelMath+4MAS-Zero: Designing Multi-Agent Systems with Zero Supervision
Multi-agent systems (MAS) leveraging the impressive capabilities of Large Language Models (LLMs) hold significant potential for tackling complex tasks. However, most current MAS depend on manually designed agent roles an…
MathProblem DecompositionAI4Math: A Native Spanish Benchmark for University-Level Mathematical Reasoning in Large Language Models
Existing mathematical reasoning benchmarks are predominantly English only or translation-based, which can introduce semantic drift and mask languagespecific reasoning errors. To address this, we present AI4Math, a benchm…
MathMathematical ReasoningMMATH: A Multilingual Benchmark for Mathematical Reasoning
The advent of large reasoning models, such as OpenAI o1 and DeepSeek R1, has significantly advanced complex reasoning tasks. However, their capabilities in multilingual complex reasoning remain underexplored, with existi…
MathMathematical ReasoningAnchored Diffusion Language Model
Diffusion Language Models (DLMs) promise parallel generation and bidirectional context, yet they underperform autoregressive (AR) models in both likelihood modeling and generated text quality. We identify that this perfo…
Language ModelingLanguage ModellingMathmodel+1MSA at BEA 2025 Shared Task: Disagreement-Aware Instruction Tuning for Multi-Dimensional Evaluation of LLMs as Math Tutors
We present MSA-MathEval, our submission to the BEA 2025 Shared Task on evaluating AI tutor responses across four instructional dimensions: Mistake Identification, Mistake Location, Providing Guidance, and Actionability. …
Language ModelingLanguage ModellingMathHow Is LLM Reasoning Distracted by Irrelevant Context? An Analysis Using a Controlled Benchmark
We introduce Grade School Math with Distracting Context (GSM-DC), a synthetic benchmark to evaluate Large Language Models' (LLMs) reasoning robustness against systematically controlled irrelevant context (IC). GSM-DC con…
MathOn the Effect of Negative Gradient in Group Relative Deep Reinforcement Optimization
Reinforcement learning (RL) has become popular in enhancing the reasoning capabilities of large language models (LLMs), with Group Relative Policy Optimization (GRPO) emerging as a widely used algorithm in recent systems…
MathReinforcement Learning (RL)Does Representation Intervention Really Identify Desired Concepts and Elicit Alignment?
Representation intervention aims to locate and modify the representations that encode the underlying concepts in Large Language Models (LLMs) to elicit the aligned and expected behaviors. Despite the empirical success, i…
Code GenerationMathSafety AlignmentSteering LLM Reasoning Through Bias-Only Adaptation
Recent work on reasoning-oriented language models, exemplified by o1-like systems, suggests that reinforcement-learning (RL) finetuning does not create new capabilities but instead strengthens reasoning patterns already …
GSM8KMathReinforcement Learning (RL)Enumerate-Conjecture-Prove: Formally Solving Answer-Construction Problems in Math Competitions
Mathematical reasoning lies at the heart of artificial intelligence, underpinning applications in education, program verification, and research-level mathematical discovery. Mathematical competitions, in particular, pres…
Automated Theorem ProvingMathMathematical ReasoningThe Unreasonable Effectiveness of Model Merging for Cross-Lingual Transfer in LLMs
Large language models (LLMs) still struggle across tasks outside of high-resource languages. In this work, we investigate cross-lingual transfer to lower-resource languages where task-specific post-training data is scarc…
Cross-Lingual TransferMathMathematical ReasoningRaDeR: Reasoning-aware Dense Retrieval Models
We propose RaDeR, a set of reasoning-based dense retrieval models trained with data derived from mathematical problem solving using large language models (LLMs). Our method leverages retrieval-augmented reasoning traject…
MathMathematical Problem-SolvingMathematical ReasoningRetrievalOutcome-based Reinforcement Learning to Predict the Future
Reinforcement learning with verifiable rewards (RLVR) has boosted math and coding in large language models, yet there has been little effort to extend RLVR into messier, real-world domains like forecasting. One sticking …
Holdout SetMathreinforcement-learningReinforcement LearningTowards Revealing the Effectiveness of Small-Scale Fine-tuning in R1-style Reinforcement Learning
R1-style Reinforcement Learning (RL) significantly enhances Large Language Models' reasoning capabilities, yet the mechanism behind rule-based RL remains unclear. We found that small-scale SFT has significant influence o…
MathReinforcement Learning (RL)