RobustFT: Robust Supervised Fine-tuning for Large Language Models under Noisy Response
Paper
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2412.14922
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Published
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78
december papers
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B-STaR: Monitoring and Balancing Exploration and Exploitation in Self-Taught Reasoners
Paper • 2412.17256 • Published • 35 -
OpenAI o1 System Card
Paper • 2412.16720 • Published • 22 -
Revisiting In-Context Learning with Long Context Language Models
Paper • 2412.16926 • Published • 21 -
Qwen2.5 Technical Report
Paper • 2412.15115 • Published • 328 -
How to Synthesize Text Data without Model Collapse?
Paper • 2412.14689 • Published • 45 -
Thinking in Space: How Multimodal Large Language Models See, Remember, and Recall Spaces
Paper • 2412.14171 • Published • 22 -
Alignment faking in large language models
Paper • 2412.14093 • Published • 7 -
Byte Latent Transformer: Patches Scale Better Than Tokens
Paper • 2412.09871 • Published • 76 -
Apollo: An Exploration of Video Understanding in Large Multimodal Models
Paper • 2412.10360 • Published • 131 -
Phi-4 Technical Report
Paper • 2412.08905 • Published • 92 -
Evaluating and Aligning CodeLLMs on Human Preference
Paper • 2412.05210 • Published • 47 -
Hidden in the Noise: Two-Stage Robust Watermarking for Images
Paper • 2412.04653 • Published • 28 -
Training Large Language Models to Reason in a Continuous Latent Space
Paper • 2412.06769 • Published • 62 -
Evaluating Language Models as Synthetic Data Generators
Paper • 2412.03679 • Published • 43 -
Surveying the Effects of Quality, Diversity, and Complexity in Synthetic Data From Large Language Models
Paper • 2412.02980 • Published • 12 -
Reverse Thinking Makes LLMs Stronger Reasoners
Paper • 2411.19865 • Published • 19