activity
20212026
most citedESC: Exploration with Soft Commonsense Constraints for Zero-shot Object Navigation

23 citations · 26 across the 10 of their papers we have counts for

collaborators

10 papers

cs.LG2026

When Load-Balancing Goes Too Far: Expert Pruning in Over-Dispersed Mixture-of-Experts Models

Berkcan Kapusuzoglu, Connor Pryor, Sangwoo Cho +4

Expert pruning reduces the memory and serving cost of Mixture-of-Experts (MoE) models by removing low-importance experts identified by the router, assuming router probabilities pro…

cs.LG2024

A Mathematical Framework and a Suite of Learning Techniques for Neural-Symbolic Systems

Charles Dickens, Connor Pryor, Changyu Gao +5

The field of Neural-Symbolic (NeSy) systems is growing rapidly. Proposed approaches show great promise in achieving symbiotic unions of neural and symbolic methods. However, a unif…

cs.CL2024

Using Domain Knowledge to Guide Dialog Structure Induction via Neural Probabilistic Soft Logic

Connor Pryor, Quan Yuan, Jeremiah Liu +4

Dialog Structure Induction (DSI) is the task of inferring the latent dialog structure (i.e., a set of dialog states and their temporal transitions) of a given goal-oriented dialog.…

cs.LG2024★ 1 cited

Convex and Bilevel Optimization for Neuro-Symbolic Inference and Learning

Charles Dickens, Changyu Gao, Connor Pryor +2

We leverage convex and bilevel optimization techniques to develop a general gradient-based parameter learning framework for neural-symbolic (NeSy) systems. We demonstrate our frame…

cs.AI2023★ 23 cited

ESC: Exploration with Soft Commonsense Constraints for Zero-shot Object Navigation

Kaiwen Zhou, Kaizhi Zheng, Connor Pryor +4

The ability to accurately locate and navigate to a specific object is a crucial capability for embodied agents that operate in the real world and interact with objects to complete…

cs.CL2022

CausalDialogue: Modeling Utterance-level Causality in Conversations

Yi-Lin Tuan, Alon Albalak, Wenda Xu +4

Despite their widespread adoption, neural conversation models have yet to exhibit natural chat capabilities with humans. In this research, we examine user utterances as causes and…

cs.LG2022★ 1 cited

Emotion Recognition in Conversation using Probabilistic Soft Logic

Eriq Augustine, Pegah Jandaghi, Alon Albalak +4

Creating agents that can both appropriately respond to conversations and understand complex human linguistic tendencies and social cues has been a long standing challenge in the NL…

cs.LG2022★ 1 cited

NeuPSL: Neural Probabilistic Soft Logic

Connor Pryor, Charles Dickens, Eriq Augustine +3

In this paper, we introduce Neural Probabilistic Soft Logic (NeuPSL), a novel neuro-symbolic (NeSy) framework that unites state-of-the-art symbolic reasoning with the low-level per…

cs.CL2022

FETA: A Benchmark for Few-Sample Task Transfer in Open-Domain Dialogue

Alon Albalak, Yi-Lin Tuan, Pegah Jandaghi +6

Task transfer, transferring knowledge contained in related tasks, holds the promise of reducing the quantity of labeled data required to fine-tune language models. Dialogue underst…

cs.CL2021

Local Explanation of Dialogue Response Generation

Yi-Lin Tuan, Connor Pryor, Wenhu Chen +2

In comparison to the interpretation of classification models, the explanation of sequence generation models is also an important problem, however it has seen little attention. In t…