2 citations · 2 across the 7 of their papers we have counts for
4 papers · 1 filter
Graph-based Uncertainty Metrics for Long-form Language Model Outputs
Mingjian Jiang, Yangjun Ruan, Prasanna Sattigeri +2
Recent advancements in Large Language Models (LLMs) have significantly improved text generation capabilities, but these systems are still known to hallucinate, and granular uncerta…
Locality Alignment Improves Vision-Language Models
Ian Covert, Tony Sun, James Zou +1
Vision language models (VLMs) have seen growing adoption in recent years, but many still struggle with basic spatial reasoning errors. We hypothesize that this is due to VLMs adopt…
Scaling Laws for the Value of Individual Data Points in Machine Learning
Ian Covert, Wenlong Ji, Tatsunori Hashimoto +1
Recent works have shown that machine learning models improve at a predictable rate with the total amount of training data, leading to scaling laws that describe the relationship be…
Observational Scaling Laws and the Predictability of Language Model Performance
Yangjun Ruan, Chris J. Maddison, Tatsunori Hashimoto
Understanding how language model performance varies with scale is critical to benchmark and algorithm development. Scaling laws are one approach to building this understanding, but…