94 citations · 449 across the 53 of their papers we have counts for
10 papers · 1 filter
On a Foundation Model for Operating Systems
Divyanshu Saxena, Nihal Sharma, Donghyun Kim +15
This paper lays down the research agenda for a domain-specific foundation model for operating systems (OSes). Our case for a foundation model revolves around the observations that…
MuSR: Testing the Limits of Chain-of-thought with Multistep Soft Reasoning
Zayne Sprague, Xi Ye, Kaj Bostrom +2
While large language models (LLMs) equipped with techniques like chain-of-thought prompting have demonstrated impressive capabilities, they still fall short in their ability to rea…
Neurosymbolic Grounding for Compositional World Models
Atharva Sehgal, Arya Grayeli, Jennifer J. Sun +1
We introduce Cosmos, a framework for object-centric world modeling that is designed for compositional generalization (CompGen), i.e., high performance on unseen input scenes obtain…
Automata Learning from Preference and Equivalence Queries
Eric Hsiung, Joydeep Biswas, Swarat Chaudhuri
Active automata learning from membership and equivalence queries is a foundational problem with numerous applications. We propose a novel variant of the active automata learning pr…
Deductive Additivity for Planning of Natural Language Proofs
Zayne Sprague, Kaj Bostrom, Swarat Chaudhuri +1
Current natural language systems designed for multi-step claim validation typically operate in two phases: retrieve a set of relevant premise statements using heuristics (planning)…
A Probabilistic Framework for Modular Continual Learning
Lazar Valkov, Akash Srivastava, Swarat Chaudhuri +1
Modular approaches that use a different composition of modules for each problem are a promising direction in continual learning (CL). However, searching through the large, discrete…
Coarse-Tuning Models of Code with Reinforcement Learning Feedback
Abhinav Jain, Chima Adiole, Swarat Chaudhuri +2
Large Language Models (LLMs) pre-trained on code have recently emerged as the dominant approach to program synthesis. However, these models are trained using next-token prediction,…
Weighted Context-Free-Language Ordered Binary Decision Diagrams
Meghana Sistla, Swarat Chaudhuri, Thomas Reps
This paper presents a new data structure, called \emph{Weighted Context-Free-Language Ordered BDDs} (WCFLOBDDs), which are a hierarchically structured decision diagram, akin to Wei…
Symbolic Quantum Simulation with Quasimodo
Meghana Sistla, Swarat Chaudhuri, Thomas Reps
The simulation of quantum circuits on classical computers is an important problem in quantum computing. Such simulation requires representations of distributions over very large se…
Certifiably Robust Reinforcement Learning through Model-Based Abstract Interpretation
Chenxi Yang, Greg Anderson, Swarat Chaudhuri
We present a reinforcement learning (RL) framework in which the learned policy comes with a machine-checkable certificate of provable adversarial robustness. Our approach, called C…