[논문리뷰] SWE-Lego: Pushing the Limits of Supervised Fine-tuning for Software Issue ResolvingarXiv에 게시된 'SWE-Lego: Pushing the Limits of Supervised Fine-tuning for Software Issue Resolving' 논문에 대한 자세한 리뷰입니다.#Review#Software Engineering#Issue Resolution#Supervised Fine-tuning (SFT)#Large Language Models (LLMs)#Hybrid Dataset#Error Masking#Curriculum Learning#Test-Time Scaling (TTS)#Generative Verifiers2026년 1월 5일댓글 수 로딩 중
[논문리뷰] Falcon-H1R: Pushing the Reasoning Frontiers with a Hybrid Model for Efficient Test-Time ScalingarXiv에 게시된 'Falcon-H1R: Pushing the Reasoning Frontiers with a Hybrid Model for Efficient Test-Time Scaling' 논문에 대한 자세한 리뷰입니다.#Review#Reasoning#Small Language Models (SLMs)#Hybrid Architecture#Test-Time Scaling (TTS)#Supervised Fine-Tuning (SFT)#Reinforcement Learning (RL)#DeepConf#Computational Efficiency2026년 1월 5일댓글 수 로딩 중
[논문리뷰] Video-LMM Post-Training: A Deep Dive into Video Reasoning with Large Multimodal Modelszeliang0426이 arXiv에 게시한 'Video-LMM Post-Training: A Deep Dive into Video Reasoning with Large Multimodal Models' 논문에 대한 자세한 리뷰입니다.#Review#Video Reasoning#Large Multimodal Models (LMMs)#Post-training#Supervised Fine-tuning (SFT)#Reinforcement Learning (RL)#Test-Time Scaling (TTS)#Chain-of-Thought (CoT)2025년 10월 7일댓글 수 로딩 중
[논문리뷰] Training Vision-Language Process Reward Models for Test-Time Scaling in Multimodal Reasoning: Key Insights and Lessons LearnedarXiv에 게시된 'Training Vision-Language Process Reward Models for Test-Time Scaling in Multimodal Reasoning: Key Insights and Lessons Learned' 논문에 대한 자세한 리뷰입니다.#Review#Vision-Language Models (VLMs)#Process Reward Models (PRMs)#Multimodal Reasoning#Test-Time Scaling (TTS)#Process Supervision#Dataset Construction#Perception Errors#MCTS2025년 10월 2일댓글 수 로딩 중