Search Results for author:
Found 9 papers, 3 papers with code
Evaluating Robustness of Dialogue Summarization Models in the Presence of Naturally Occurring Variations
We find that both fine-tuned and instruction-tuned models are affected by input variations, with the latter being more susceptible, particularly to dialogue-level perturbations.
Examining Political Rhetoric with Epistemic Stance Detection
Participants in political discourse employ rhetorical strategies -- such as hedging, attributions, or denials -- to display varying degrees of belief commitments to claims proposed by themselves or others.
DEMETR: Diagnosing Evaluation Metrics for Translation
While machine translation evaluation metrics based on string overlap (e. g., BLEU) have their limitations, their computations are transparent: the BLEU score assigned to a particular candidate translation can be traced back to the presence or absence of certain words.
ezCoref: Towards Unifying Annotation Guidelines for Coreference Resolution
Large-scale, high-quality corpora are critical for advancing research in coreference resolution.
Solomon at SemEval-2020 Task 11: Ensemble Architecture for Fine-Tuned Propaganda Detection in News Articles
This paper describes our system (Solomon) details and results of participation in the SemEval 2020 Task 11 "Detection of Propaganda Techniques in News Articles"\cite{DaSanMartinoSemeval20task11}.
NarrativeTime: Dense Temporal Annotation on a Timeline
For the past decade, temporal annotation has been sparse: only a small portion of event pairs in a text was annotated.
MSIT\_SRIB at MEDIQA 2019: Knowledge Directed Multi-task Framework for Natural Language Inference in Clinical Domain.
In this paper, we present Biomedical Multi-Task Deep Neural Network (Bio-MTDNN) on the NLI task of MediQA 2019 challenge.
SolomonLab at SemEval-2019 Task 8: Question Factuality and Answer Veracity Prediction in Community Forums
We describe our system for SemEval-2019, Task 8 on {``}Fact-Checking in Community Question Answering Forums (cQA){''}.
Vernon-fenwick at SemEval-2019 Task 4: Hyperpartisan News Detection using Lexical and Semantic Features
In this paper, we present our submission for SemEval-2019 Task 4: Hyperpartisan News Detection.
