2.3k citations · 4.7k across the 88 of their papers we have counts for
17 papers · 1 filter
Task Ambiguity in Humans and Language Models
Alex Tamkin, Kunal Handa, Avash Shrestha +1
Language models have recently achieved strong performance across a wide range of NLP benchmarks. However, unlike benchmarks, real world tasks are often poorly specified, and agents…
Feature Dropout: Revisiting the Role of Augmentations in Contrastive Learning
Alex Tamkin, Margalit Glasgow, Xiluo He +1
What role do augmentations play in contrastive learning? Recent work suggests that good augmentations are label-preserving with respect to a specific downstream task. We complicate…
Parsel: Algorithmic Reasoning with Language Models by Composing Decompositions
Eric Zelikman, Qian Huang, Gabriel Poesia +2
Despite recent success in large language model (LLM) reasoning, LLMs struggle with hierarchical multi-step reasoning tasks like generating complex programs. For these tasks, humans…
Flexible social inference facilitates targeted social learning when rewards are not observable
Robert D. Hawkins, Andrew M. Berdahl, Alex "Sandy" Pentland +3
Groups coordinate more effectively when individuals are able to learn from others' successes. But acquiring such knowledge is not always easy, especially in real-world environments…
Geoclidean: Few-Shot Generalization in Euclidean Geometry
Joy Hsu, Jiajun Wu, Noah D. Goodman
Euclidean geometry is among the earliest forms of mathematical thinking. While the geometric primitives underlying its constructions, such as perfect lines and circles, do not ofte…
Peano: Learning Formal Mathematical Reasoning
Gabriel Poesia, Noah D. Goodman
General mathematical reasoning is computationally undecidable, but humans routinely solve new problems. Moreover, discoveries developed over centuries are taught to subsequent gene…