Papers Math
“Math” 태그가 달린 논문 1,596편 · 필터 해제
Infi-MMR: Curriculum-based Unlocking Multimodal Reasoning via Phased Reinforcement Learning in Multimodal Small Language Models
Recent advancements in large language models (LLMs) have demonstrated substantial progress in reasoning capabilities, such as DeepSeek-R1, which leverages rule-based reinforcement learning to enhance logical reasoning si…
Logical ReasoningMathMultimodal ReasoningMathArena: Evaluating LLMs on Uncontaminated Math Competitions
The rapid advancement of reasoning capabilities in large language models (LLMs) has led to notable improvements on mathematical benchmarks. However, many of the most commonly used evaluation datasets (e.g., AIME 2024) ar…
MathMathematical ReasoningMemorizationLet's Reason Formally: Natural-Formal Hybrid Reasoning Enhances LLM's Math Capability
Enhancing the mathematical reasoning capabilities of LLMs has garnered significant attention in both the mathematical and computer science communities. Recent works have made substantial progress in both Natural Language…
MathMathematical ReasoningQuestion AnsweringReinforcement Learning (RL)ChatVLA-2: Vision-Language-Action Model with Open-World Embodied Reasoning from Pretrained Knowledge
Vision-language-action (VLA) models have emerged as the next generation of models in robotics. However, despite leveraging powerful pre-trained Vision-Language Models (VLMs), existing end-to-end VLA systems often lose ke…
Imitation LearningMathMathematical ReasoningOptical Character Recognition (OCR)+2Decomposing Elements of Problem Solving: What "Math" Does RL Teach?
Mathematical reasoning tasks have become prominent benchmarks for assessing the reasoning capabilities of LLMs, especially with reinforcement learning (RL) methods such as GRPO showing significant performance gains. Howe…
MathMathematical Problem-SolvingMathematical ReasoningReinforcement Learning (RL)Skywork Open Reasoner 1 Technical Report
The success of DeepSeek-R1 underscores the significant role of reinforcement learning (RL) in enhancing the reasoning capabilities of large language models (LLMs). In this work, we present Skywork-OR1, an effective and s…
MathReinforcement Learning (RL)Maximizing Confidence Alone Improves Reasoning
Reinforcement learning (RL) has enabled machine learning models to achieve significant advances in many fields. Most recently, RL has empowered frontier language models to solve challenging math, science, and coding prob…
GSM8KMathreinforcement-learningReinforcement Learning+1Unsupervised Post-Training for Multi-Modal LLM Reasoning via GRPO
Improving Multi-modal Large Language Models (MLLMs) in the post-training stage typically relies on supervised fine-tuning (SFT) or reinforcement learning (RL). However, these supervised methods require expensive and manu…
MathReinforcement Learning (RL)Advancing Multimodal Reasoning via Reinforcement Learning with Cold Start
Recent advancements in large language models (LLMs) have demonstrated impressive chain-of-thought reasoning capabilities, with reinforcement learning (RL) playing a crucial role in this progress. While "aha moment" patte…
MathMultimodal Reasoningreinforcement-learningReinforcement Learning+1ASyMOB: Algebraic Symbolic Mathematical Operations Benchmark
Large language models (LLMs) are rapidly approaching the level of proficiency in university-level symbolic mathematics required for applications in advanced science and technology. However, existing benchmarks fall short…
MathREAL-Prover: Retrieval Augmented Lean Prover for Mathematical Reasoning
Nowadays, formal theorem provers have made monumental progress on high-school and competition-level mathematics, but few of them generalize to more advanced mathematics. In this paper, we present REAL-Prover, a new open-…
Language ModelingLanguage ModellingLarge Language ModelMath+2R2R: Efficiently Navigating Divergent Reasoning Paths with Small-Large Model Token Routing
Large Language Models (LLMs) achieve impressive reasoning capabilities at the cost of substantial inference overhead, posing substantial deployment challenges. Although distilled Small Language Models (SLMs) significantl…
MathWalk Before You Run! Concise LLM Reasoning via Reinforcement Learning
As test-time scaling becomes a pivotal research frontier in Large Language Models (LLMs) development, contemporary and advanced post-training methodologies increasingly focus on extending the generation length of long Ch…
MathReinforcing General Reasoning without Verifiers
The recent paradigm shift towards training large language models (LLMs) using DeepSeek-R1-Zero-style reinforcement learning (RL) on verifiable rewards has led to impressive advancements in code and mathematical reasoning…
MathMathematical ReasoningMMLUReinforcement Learning (RL)Hard Negative Contrastive Learning for Fine-Grained Geometric Understanding in Large Multimodal Models
Benefiting from contrastively trained visual encoders on large-scale natural scene images, Large Multimodal Models (LMMs) have achieved remarkable performance across various visual perception tasks. However, the inherent…
Contrastive LearningMathThe Role of Diversity in In-Context Learning for Large Language Models
In-context learning (ICL) is a crucial capability of current large language models (LLMs), where the selection of examples plays a key role in performance. While most existing approaches focus on selecting the most simil…
DiversityIn-Context LearningMathSentiment Analysis+1Faster and Better LLMs via Latency-Aware Test-Time Scaling
Test-Time Scaling (TTS) has proven effective in improving the performance of Large Language Models (LLMs) during inference. However, existing research has overlooked the efficiency of TTS from a latency-sensitive perspec…
MathInterleaved Reasoning for Large Language Models via Reinforcement Learning
Long chain-of-thought (CoT) significantly enhances large language models' (LLM) reasoning capabilities. However, the extensive reasoning traces lead to inefficiencies and an increased time-to-first-token (TTFT). We propo…
Logical ReasoningMathMMLUQuestion Answering+3Error Typing for Smarter Rewards: Improving Process Reward Models with Error-Aware Hierarchical Supervision
Large Language Models (LLMs) are prone to hallucination, especially during multi-hop and reasoning-intensive tasks such as mathematical problem solving. While Outcome Reward Models verify only final answers, Process Rewa…
HallucinationMathMathematical Problem-SolvingMathematical Reasoning+1Improving Multilingual Math Reasoning for African Languages
Researchers working on low-resource languages face persistent challenges due to limited data availability and restricted access to computational resources. Although most large language models (LLMs) are predominantly tra…
MathMathematical Reasoning