HuggingFace has upgraded the Open LLM Leaderboard to v2, adding new benchmarks and improving the evaluation suite for easier reproducibility.
Gemma 2, a new addition to the Gemma family of lightweight open models, delivers the best performance for its size and offers competitive alternatives to models that are 2-3× bigger.
SeaKR is a new model that re-ranks retrieved knowledge based on the LLM's self-aware uncertainty, outperforming existing adaptive RAG methods in generating text with relevant and accurate information.
Step-DPO is a new method that enhances the robustness and factuality of LLMs by learning from human feedback, achieving impressive results in long-chain mathematical reasoning.
Contact:  [email protected]
Timestamps:
00:34 Introduction
01:21 HuggingFace Updates Open LLM Leaderboard
03:19 Gemma 2: Improving Open Language Models at a Practical Size
04:16 From bare metal to a 70B model: infrastructure set-up and scripts
05:21 Fake sponsor
07:11 SeaKR: Self-aware Knowledge Retrieval for Adaptive Retrieval Augmented Generation
08:47 Simulating Classroom Education with LLM-Empowered Agents
10:16 Step-DPO: Step-wise Preference Optimization for Long-chain Reasoning of LLMs
12:31 Outro

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