91 citations · 101 across the 6 of their papers we have counts for
7 papers
MDBench: A Synthetic Multi-Document Reasoning Benchmark Generated with Knowledge Guidance
Joseph J. Peper, Wenzhao Qiu, Ali Payani +1
Natural language processing evaluation has made significant progress, largely driven by the proliferation of powerful large language mod-els (LLMs). New evaluation benchmarks are o…
Evaluation Framework for AI Systems in "the Wild"
Sarah Jabbour, Trenton Chang, Anindya Das Antar +13
Generative AI (GenAI) models have become vital across industries, yet current evaluation methods have not adapted to their widespread use. Traditional evaluations often rely on ben…
PELMS: Pre-training for Effective Low-Shot Multi-Document Summarization
Joseph J. Peper, Wenzhao Qiu, Lu Wang
We investigate pre-training techniques for abstractive multi-document summarization (MDS), which is much less studied than summarizing single documents. Though recent work has demo…
Generative Aspect-Based Sentiment Analysis with Contrastive Learning and Expressive Structure
Joseph J. Peper, Lu Wang
Generative models have demonstrated impressive results on Aspect-based Sentiment Analysis (ABSA) tasks, particularly for the emerging task of extracting Aspect-Category-Opinion-Sen…
One Agent To Rule Them All: Towards Multi-agent Conversational AI
Christopher Clarke, Joseph Joshua Peper, Karthik Krishnamurthy +6
The increasing volume of commercially available conversational agents (CAs) on the market has resulted in users being burdened with learning and adopting multiple agents to accompl…
An Evaluation Dataset for Intent Classification and Out-of-Scope Prediction
Stefan Larson, Anish Mahendran, Joseph J. Peper +8
Task-oriented dialog systems need to know when a query falls outside their range of supported intents, but current text classification corpora only define label sets that cover eve…
A Large-Scale Corpus for Conversation Disentanglement
Jonathan K. Kummerfeld, Sai R. Gouravajhala, Joseph Peper +6
Disentangling conversations mixed together in a single stream of messages is a difficult task, made harder by the lack of large manually annotated datasets. We created a new datase…