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Retrv-R1: A Reasoning-Driven MLLM Framework for Universal and Efficient Multimodal Retrieval
Arxiv
0+阅读 · 10月3日
ConciseHint: Boosting Efficient Reasoning via Continuous Concise Hints during Generation
Arxiv
0+阅读 · 10月1日
Diamonds in the rough: Transforming SPARCs of imagination into a game concept by leveraging medium sized LLMs
Arxiv
0+阅读 · 9月29日
FAMMA: A Benchmark for Financial Domain Multilingual Multimodal Question Answering
Arxiv
0+阅读 · 5月14日
FAMMA: A Benchmark for Financial Domain Multilingual Multimodal Question Answering
Arxiv
0+阅读 · 5月15日
Explainable Sentiment Analysis with DeepSeek-R1: Performance, Efficiency, and Few-Shot Learning
Arxiv
0+阅读 · 6月30日
Explainable Sentiment Analysis with DeepSeek-R1: Performance, Efficiency, and Few-Shot Learning
Arxiv
0+阅读 · 8月14日
Domain-Specific Pruning of Large Mixture-of-Experts Models with Few-shot Demonstrations
Arxiv
0+阅读 · 4月9日
Light-R1: Curriculum SFT, DPO and RL for Long COT from Scratch and Beyond
Light-R1: Curriculum SFT, DPO and RL for Long COT from Scratch and Beyond
Arxiv
0+阅读 · 4月1日
Safety Evaluation and Enhancement of DeepSeek Models in Chinese Contexts
Arxiv
0+阅读 · 3月18日
Quantifying the Reasoning Abilities of LLMs on Real-world Clinical Cases
Arxiv
0+阅读 · 3月10日
Quantifying the Reasoning Abilities of LLMs on Real-world Clinical Cases
Arxiv
0+阅读 · 3月6日
LADDER: Self-Improving LLMs Through Recursive Problem Decomposition
Arxiv
0+阅读 · 3月5日
LADDER: Self-Improving LLMs Through Recursive Problem Decomposition
Arxiv
0+阅读 · 3月4日
Fin-R1: A Large Language Model for Financial Reasoning through Reinforcement Learning
Arxiv
0+阅读 · 3月20日
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