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Found 3 papers, 2 papers with code
Long-form factuality in large language models
Empirically, we demonstrate that LLM agents can outperform crowdsourced human annotators - on a set of ~16k individual facts, SAFE agrees with crowdsourced human annotators 72% of the time, and on a random subset of 100 disagreement cases, SAFE wins 76% of the time.
Meta-Learning Online Adaptation of Language Models
We meta-train a small, autoregressive model to reweight the language modeling loss for each token during online fine-tuning, with the objective of maximizing the out-of-date base question-answering model's ability to answer questions about a document after a single weighted gradient step.
Sampling Arborescences in Parallel
For several well-studied combinatorial structures, counting can be reduced to the computation of a determinant, which is known to be in NC [Csa75].
Point Processes
Data Structures and Algorithms
Combinatorics
Probability
