35 citations · 91 across the 14 of their papers we have counts for
6 papers · 1 filter
The Truth is in There: Improving Reasoning in Language Models with Layer-Selective Rank Reduction
Pratyusha Sharma, Jordan T. Ash, Dipendra Misra
Transformer-based Large Language Models (LLMs) have become a fixture in modern machine learning. Correspondingly, significant resources are allocated towards research that aims to…
Learning adaptive planning representations with natural language guidance
Lionel Wong, Jiayuan Mao, Pratyusha Sharma +5
Effective planning in the real world requires not only world knowledge, but the ability to leverage that knowledge to build the right representation of the task at hand. Decades of…
Pushdown Layers: Encoding Recursive Structure in Transformer Language Models
Shikhar Murty, Pratyusha Sharma, Jacob Andreas +1
Recursion is a prominent feature of human language, and fundamentally challenging for self-attention due to the lack of an explicit recursive-state tracking mechanism. Consequently…
Pseudointelligence: A Unifying Framework for Language Model Evaluation
Shikhar Murty, Orr Paradise, Pratyusha Sharma
With large language models surpassing human performance on an increasing number of benchmarks, we must take a principled approach for targeted evaluation of model capabilities. Ins…
Grokking of Hierarchical Structure in Vanilla Transformers
Shikhar Murty, Pratyusha Sharma, Jacob Andreas +1
For humans, language production and comprehension is sensitive to the hierarchical structure of sentences. In natural language processing, past work has questioned how effectively…
LaMPP: Language Models as Probabilistic Priors for Perception and Action
Belinda Z. Li, William Chen, Pratyusha Sharma +1
Language models trained on large text corpora encode rich distributional information about real-world environments and action sequences. This information plays a crucial role in cu…