[논문리뷰] OptiMer: Optimal Distribution Vector Merging Is Better than Data Mixing for Continual Pre-TrainingarXiv에 게시된 'OptiMer: Optimal Distribution Vector Merging Is Better than Data Mixing for Continual Pre-Training' 논문에 대한 자세한 리뷰입니다.#Review#Continual Pre-training#Model Merging#Distribution Vector#Bayesian Optimization#LLM Adaptation2026년 3월 31일댓글 수 로딩 중
[논문리뷰] DataChef: Cooking Up Optimal Data Recipes for LLM Adaptation via Reinforcement LearningKai Chen이 arXiv에 게시한 'DataChef: Cooking Up Optimal Data Recipes for LLM Adaptation via Reinforcement Learning' 논문에 대한 자세한 리뷰입니다.#Review#LLM Adaptation#Reinforcement Learning#Data Curation#Data Pipelines#Data Recipes#Data Verifier#Data-centric AI2026년 2월 11일댓글 수 로딩 중
[논문리뷰] ASA: Training-Free Representation Engineering for Tool-Calling AgentsHongwei Zeng이 arXiv에 게시한 'ASA: Training-Free Representation Engineering for Tool-Calling Agents' 논문에 대한 자세한 리뷰입니다.#Review#Tool-Calling Agents#LLM Adaptation#Representation Engineering#Activation Steering#Training-Free#Inference-Time Control#Domain Adaptation2026년 2월 11일댓글 수 로딩 중
[논문리뷰] Evaluating Parameter Efficient Methods for RLVRarXiv에 게시된 'Evaluating Parameter Efficient Methods for RLVR' 논문에 대한 자세한 리뷰입니다.#Review#Parameter-Efficient Fine-Tuning (PEFT)#Reinforcement Learning with Verifiable Rewards (RLVR)#Low-Rank Adaptation (LoRA)#Mathematical Reasoning#LLM Adaptation#SVD Initialization2025년 12월 30일댓글 수 로딩 중
[논문리뷰] From Next-Token to Next-Block: A Principled Adaptation Path for Diffusion LLMsarXiv에 게시된 'From Next-Token to Next-Block: A Principled Adaptation Path for Diffusion LLMs' 논문에 대한 자세한 리뷰입니다.#Review#Diffusion Language Models#LLM Adaptation#Block-Diffusion#Autoregressive Models#Attention Masks#Parallel Generation#Transfer Learning#Generative Models2025년 12월 9일댓글 수 로딩 중