Large Language Model
LLM Evaluators Recognize and Favor Their Own Generations
But new biases are introduced due to the same LLM acting as both the evaluator and the evaluatee.
FlashAttention-3: Fast and Accurate Attention with Asynchrony and Low-precision Jay Shah
In this work, we build on the work of Dao et al.
Quantitatively Understanding the Bitter Lesson Through Capabilities Trajectories
In an extensive analysis of existing safety benchmarks, we find that variance in model performance on many safety benchmarks is largely explained by the capabilities component.
ZipCache: Accurate and Efficient KV Cache Quantization with Salient Token Identification Y efei He
KV cache compression seeks to discern the saliency of tokens, preserving vital information while aggressively compressing those of less importance.
BLoB: Bayesian Low-Rank Adaptation by Backpropagation for Large Language Models Yibin Wang
Current research predominantly focuses on eliciting the internal capability of uncertainty estimation of LLMs.
Generating a Diversity of Challenging Programming Puzzles with Autotelic Generative Models
Chen et al., 2021], and come up with new problems that drive innovation in art and science [Gromov,