OceanPile is a new multimodal corpus with unified data collection, instruction tuning set, and benchmark to train foundation models for ocean science.
LlamaV-o1: Rethinking Step-by-step Visual Reasoning in LLMs
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Saliency-R1 uses a novel saliency map technique and GRPO with human bounding-box overlap as reward to improve VLM reasoning faithfulness and interpretability.
The survey organizes the shift of LLMs toward deliberate System 2 reasoning, covering model construction techniques, performance on math and coding benchmarks, and future research directions.
citing papers explorer
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OceanPile: A Large-Scale Multimodal Ocean Corpus for Foundation Models
OceanPile is a new multimodal corpus with unified data collection, instruction tuning set, and benchmark to train foundation models for ocean science.
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Saliency-R1: Enforcing Interpretable and Faithful Vision-language Reasoning via Saliency-map Alignment Reward
Saliency-R1 uses a novel saliency map technique and GRPO with human bounding-box overlap as reward to improve VLM reasoning faithfulness and interpretability.
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From System 1 to System 2: A Survey of Reasoning Large Language Models
The survey organizes the shift of LLMs toward deliberate System 2 reasoning, covering model construction techniques, performance on math and coding benchmarks, and future research directions.