2 citations · 2 across the 7 of their papers we have counts for
7 papers
Will Scaling Improve Social Simulation with LLMs?
Caleb Ziems, William Held, Su Doga Karaca +3
Large Language Model (LLM) social simulations are a promising research method, but they are not yet faithful enough to be adopted widely. In this work, we investigate whether the c…
Putting It All into Context: Simplifying Agents with LCLMs
Mingjian Jiang, Yangjun Ruan, Luis Lastras +2
Recent advances in language model (LM) agents have demonstrated significant potential for automating complex real-world tasks. To make progress on these difficult tasks, LM agent a…
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…
On the Fairness ROAD: Robust Optimization for Adversarial Debiasing
Vincent Grari, Thibault Laugel, Tatsunori Hashimoto +2
In the field of algorithmic fairness, significant attention has been put on group fairness criteria, such as Demographic Parity and Equalized Odds. Nevertheless, these objectives,…