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How Does Quantization Affect Multilingual LLMs?
Paper • 2407.03211 • Published • 1 -
Coercing LLMs to do and reveal (almost) anything
Paper • 2402.14020 • Published • 13 -
RLVF: Learning from Verbal Feedback without Overgeneralization
Paper • 2402.10893 • Published • 11 -
Is Cosine-Similarity of Embeddings Really About Similarity?
Paper • 2403.05440 • Published • 3
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Collections including paper arxiv:2403.05440
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Is Cosine-Similarity of Embeddings Really About Similarity?
Paper • 2403.05440 • Published • 3 -
GISTEmbed: Guided In-sample Selection of Training Negatives for Text Embedding Fine-tuning
Paper • 2402.16829 • Published -
Make Your LLM Fully Utilize the Context
Paper • 2404.16811 • Published • 53 -
KAN: Kolmogorov-Arnold Networks
Paper • 2404.19756 • Published • 109
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Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models
Paper • 2310.04406 • Published • 8 -
Chain-of-Thought Reasoning Without Prompting
Paper • 2402.10200 • Published • 105 -
ICDPO: Effectively Borrowing Alignment Capability of Others via In-context Direct Preference Optimization
Paper • 2402.09320 • Published • 6 -
Self-Discover: Large Language Models Self-Compose Reasoning Structures
Paper • 2402.03620 • Published • 116
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PRDP: Proximal Reward Difference Prediction for Large-Scale Reward Finetuning of Diffusion Models
Paper • 2402.08714 • Published • 12 -
Data Engineering for Scaling Language Models to 128K Context
Paper • 2402.10171 • Published • 24 -
RLVF: Learning from Verbal Feedback without Overgeneralization
Paper • 2402.10893 • Published • 11 -
Coercing LLMs to do and reveal (almost) anything
Paper • 2402.14020 • Published • 13