1 citations · 2 across the 5 of their papers we have counts for
6 papers
Neurosymbolic Routing for Reliable Reasoning on Resource-Constrained Edge Devices
Avyay Sadhu, Alvaro Velasquez, Lekai Chen
Running a language model on edge hardware provides private and low-latency reasoning without a network connection, and yet the small models that fit on such devices are unreliable…
CEDAR: Automata as Verifiable Interfaces for Language-Guided Embodied Action
Lekai Chen, Alvaro Velasquez, Ashutosh Trivedi
Natural-language tasking of embodied agents is rarely just goal specification: users also impose constraints that must persist while the world changes. Code-generating LLM agents c…
KV-Fold: One-Step KV-Cache Recurrence for Long-Context Inference
Alireza Nadali, Patrick Cooper, Ashutosh Trivedi +1
We introduce KV-Fold, a simple, training-free long-context inference protocol that treats the key-value (KV) cache as the accumulator in a left fold over sequence chunks. At each s…
Average Reward Reinforcement Learning for Omega-Regular and Mean-Payoff Objectives
Milad Kazemi, Mateo Perez, Fabio Somenzi +3
Recent advances in reinforcement learning (RL) have renewed interest in reward design for shaping agent behavior, but manually crafting reward functions is tedious and error-prone.…
LLMs as Probabilistic Minimally Adequate Teachers for DFA Learning
Lekai Chen, Ashutosh Trivedi, Alvaro Velasquez
The emergence of intelligence in large language models (LLMs) has inspired investigations into their integration into automata learning. This paper introduces the probabilistic Min…
Assume-Guarantee Reinforcement Learning
Milad Kazemi, Mateo Perez, Fabio Somenzi +3
We present a modular approach to \emph{reinforcement learning} (RL) in environments consisting of simpler components evolving in parallel. A monolithic view of such modular environ…