32 citations · 92 across the 10 of their papers we have counts for
12 papers
Are We Grading Properly? Understanding Failure Modes in Medical Benchmarks
Prithvi Dixit, Pedram Hosseini
Medical evaluation is shifting from static option-based questioning to realistic clinical scenarios with open-ended output modes. Grading these at scale naively, however, is expens…
A Benchmark for Long-Form Medical Question Answering
Pedram Hosseini, Jessica M. Sin, Bing Ren +4
There is a lack of benchmarks for evaluating large language models (LLMs) in long-form medical question answering (QA). Most existing medical QA evaluation benchmarks focus on auto…
GisPy: A Tool for Measuring Gist Inference Score in Text
Pedram Hosseini, Christopher R. Wolfe, Mona Diab +1
Decision making theories such as Fuzzy-Trace Theory (FTT) suggest that individuals tend to rely on gist, or bottom-line meaning, in the text when making decisions. In this work, we…
Knowledge-Augmented Language Models for Cause-Effect Relation Classification
Pedram Hosseini, David A. Broniatowski, Mona Diab
Previous studies have shown the efficacy of knowledge augmentation methods in pretrained language models. However, these methods behave differently across domains and downstream ta…
Predicting Directionality in Causal Relations in Text
Pedram Hosseini, David A. Broniatowski, Mona Diab
In this work, we test the performance of two bidirectional transformer-based language models, BERT and SpanBERT, on predicting directionality in causal pairs in the textual content…
ParsiNLU: A Suite of Language Understanding Challenges for Persian
Daniel Khashabi, Arman Cohan, Siamak Shakeri +22
Despite the progress made in recent years in addressing natural language understanding (NLU) challenges, the majority of this progress remains to be concentrated on resource-rich l…
A Multi-Modal Method for Satire Detection using Textual and Visual Cues
Lily Li, Or Levi, Pedram Hosseini +1
Satire is a form of humorous critique, but it is sometimes misinterpreted by readers as legitimate news, which can lead to harmful consequences. We observe that the images used in…
Content analysis of Persian/Farsi Tweets during COVID-19 pandemic in Iran using NLP
Pedram Hosseini, Poorya Hosseini, David A. Broniatowski
Iran, along with China, South Korea, and Italy was among the countries that were hit hard in the first wave of the COVID-19 spread. Twitter is one of the widely-used online platfor…
Automatically Identifying Political Ads on Facebook: Towards Understanding of Manipulation via User Targeting
Or Levi, Sardar Hamidian, Pedram Hosseini
The reports of Russian interference in the 2016 United States elections brought into the center of public attention concerns related to the ability of foreign actors to increase so…
LexiPers: An ontology based sentiment lexicon for Persian
Behnam Sabeti, Pedram Hosseini, Gholamreza Ghassem-Sani +1
Sentiment analysis refers to the use of natural language processing to identify and extract subjective information from textual resources. One approach for sentiment extraction is…
Identifying Nuances in Fake News vs. Satire: Using Semantic and Linguistic Cues
Or Levi, Pedram Hosseini, Mona Diab +1
The blurry line between nefarious fake news and protected-speech satire has been a notorious struggle for social media platforms. Further to the efforts of reducing exposure to mis…
SentiPers: A Sentiment Analysis Corpus for Persian
Pedram Hosseini, Ali Ahmadian Ramaki, Hassan Maleki +2
Sentiment Analysis (SA) is a major field of study in natural language processing, computational linguistics and information retrieval. Interest in SA has been constantly growing in…