228 citations · 763 across the 17 of their papers we have counts for
9 papers · 1 filter
Mid-Harness: Scaling Actions Between Model and Harness for Terminal Agents
Minki Kang, Ryo Hachiuma, Shaokun Zhang +8
Terminal agents act through stochastic model generations, yet the ability to generate a useful action does not ensure its reliable execution. A poor command (e.g., wrong package in…
SALM-Duplex: Efficient and Direct Duplex Modeling for Speech-to-Speech Language Model
Ke Hu, Ehsan Hosseini-Asl, Chen Chen +7
Spoken dialogue is an intuitive form of human-computer interaction, yet current speech language models often remain constrained to turn-based exchanges, lacking real-time adaptabil…
Granular Change Accuracy: A More Accurate Performance Metric for Dialogue State Tracking
Taha Aksu, Nancy F. Chen
Current metrics for evaluating Dialogue State Tracking (DST) systems exhibit three primary limitations. They: i) erroneously presume a uniform distribution of slots throughout the…
A Generative Language Model for Few-shot Aspect-Based Sentiment Analysis
Ehsan Hosseini-Asl, Wenhao Liu, Caiming Xiong
Sentiment analysis is an important task in natural language processing. In recent works, pre-trained language models are often used to achieve state-of-the-art results, especially…
Joint Energy-based Model Training for Better Calibrated Natural Language Understanding Models
Tianxing He, Bryan McCann, Caiming Xiong +1
In this work, we explore joint energy-based model (EBM) training during the finetuning of pretrained text encoders (e.g., Roberta) for natural language understanding (NLU) tasks. O…
A Simple Language Model for Task-Oriented Dialogue
Ehsan Hosseini-Asl, Bryan McCann, Chien-Sheng Wu +2
Task-oriented dialogue is often decomposed into three tasks: understanding user input, deciding actions, and generating a response. While such decomposition might suggest a dedicat…
Transferable Multi-Domain State Generator for Task-Oriented Dialogue Systems
Chien-Sheng Wu, Andrea Madotto, Ehsan Hosseini-Asl +3
Over-dependence on domain ontology and lack of knowledge sharing across domains are two practical and yet less studied problems of dialogue state tracking. Existing approaches gene…
Toward Scalable Neural Dialogue State Tracking Model
Elnaz Nouri, Ehsan Hosseini-Asl
The latency in the current neural based dialogue state tracking models prohibits them from being used efficiently for deployment in production systems, albeit their highly accurate…
A Multi-Discriminator CycleGAN for Unsupervised Non-Parallel Speech Domain Adaptation
Ehsan Hosseini-Asl, Yingbo Zhou, Caiming Xiong +1
Domain adaptation plays an important role for speech recognition models, in particular, for domains that have low resources. We propose a novel generative model based on cyclic-con…