AIME
Emerging24papers using it
2025first seen
The AIME dataset/benchmark is used to evaluate the reasoning capabilities of large language models in the context of test-time scaling.
Papers using AIME (24)
- The Evolution of Thought: Tracking LLM Overthinking via Reasoning Dynamics AnalysisKimi k1.5: Scaling Reinforcement Learning with LLMsWhen LLMs Agree, Are They Right? Auditing Self-Consistency and Cross-Model Agreement as Confidence SignalsKV-PRM: Efficient Process Reward Modeling via KV-Cache Transfer for Multi-Agent Test-Time ScalingAdaptive Teacher Exposure for Self-Distillation in LLM ReasoningShare More, Search Less: Collaborative Parallel Thinking for Efficient Test-Time ScalingKVpop -- Key-Value Cache Compression with Predictive Online PruningThinkTwice: Jointly Optimizing Large Language Models for Reasoning and Self-RefinementBudget-Aware Anytime Reasoning with LLM-Synthesized Preference DataThinking on the Fly: Test-Time Reasoning Enhancement via Latent Thought Policy OptimizationDr.LLM: Dynamic Layer Routing in LLMsMemLens: Uncovering Memorization in LLMs with Activation TrajectoriesDouble-Checker: Enhancing Reasoning of Slow-Thinking LLMs via Self-Critical Fine-TuningM1: Towards Scalable Test-Time Compute with Mamba Reasoning ModelsLIMOPro: Reasoning Refinement for Efficient and Effective Test-time
ScalingEnigmata: Scaling Logical Reasoning in Large Language Models with
Synthetic Verifiable PuzzlesRing-lite: Scalable Reasoning via C3PO-Stabilized Reinforcement Learning
for LLMsEfficient Reinforcement Finetuning via Adaptive Curriculum LearningSkywork R1V: Pioneering Multimodal Reasoning with Chain-of-ThoughtReasonFlux-PRM: Trajectory-Aware PRMs for Long Chain-of-Thought
Reasoning in LLMsDoes Math Reasoning Improve General LLM Capabilities? Understanding
Transferability of LLM ReasoningCDE: Curiosity-Driven Exploration for Efficient Reinforcement Learning
in Large Language ModelsFrom Harm to Help: Turning Reasoning In-Context Demos into Assets for
Reasoning LMsDancing with Critiques: Enhancing LLM Reasoning with Stepwise Natural
Language Self-Critique