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Process reinforcement through implicit rewards
Dense process rewards have proven a more effective alternative to the sparse outcome-
level rewards in the inference-time scaling of large language models (LLMs), particularly in …
level rewards in the inference-time scaling of large language models (LLMs), particularly in …
Critique fine-tuning: Learning to critique is more effective than learning to imitate
Supervised Fine-Tuning (SFT) is commonly used to train language models to imitate
annotated responses for given instructions. In this paper, we challenge this paradigm and …
annotated responses for given instructions. In this paper, we challenge this paradigm and …
Examining False Positives under Inference Scaling for Mathematical Reasoning
Recent advancements in language models have led to significant improvements in
mathematical reasoning across various benchmarks. However, most of these benchmarks …
mathematical reasoning across various benchmarks. However, most of these benchmarks …
Digital Twin Buildings: 3D Modeling, GIS Integration, and Visual Descriptions Using Gaussian Splatting, ChatGPT/Deepseek, and Google Maps Platforms
Urban digital twins are virtual replicas of cities that use multi-source data and data analytics
to optimize urban planning, infrastructure management, and decision-making. Towards this …
to optimize urban planning, infrastructure management, and decision-making. Towards this …