Discord Questions: A Computational Approach To Diversity Analysis in News Coverage
Comments EMNLP 2022 Findings - Long Paper
期刊&会议
EMNLP
Conference on Empirical Methods in Natural Language Processing · 会议 · Natural Language Processing
Visual Named Entity Linking: A New Dataset and A Baseline
Comments 13 pages, 11 figures, published to EMNLP 2022(findings)
DORE: Document Ordered Relation Extraction based on Generative Framework
Comments Findings of EMNLP 2022
Near-Negative Distinction: Giving a Second Life to Human Evaluation Datasets
Comments EMNLP 2022 - Long Paper
The challenges of temporal alignment on Twitter during crises
Comments Accepted to Findings of EMNLP, 2022
Effective Distributed Representations for Academic Expert Search
Comments To be published in the Scholarly Document Processing 2020 Workshop @ EMNLP 2020 proceedings
Detecting Euphemisms with Literal Descriptions and Visual Imagery
Comments 7 pages, 1 table, 1 figure. Accepted to the 3rd Workshop on Figurative Language Processing at EMNLP 2022. https://github.com/ilkerkesen/euphemism
Active Example Selection for In-Context Learning
Comments EMNLP 2022, code is available at https://github.com/ChicagoHAI/active-example-selection
Discovering the Unknown Knowns: Turning Implicit Knowledge in the Dataset into Explicit Training Examples for Visual Question Answering
Comments Accepted to EMNLP 2021
Word Order Matters when you Increase Masking
Comments Accepted at EMNLP 2022 (main conference)
NaturalAdversaries: Can Naturalistic Adversaries Be as Effective as Artificial Adversaries?
Comments Findings of EMNLP 2022
SocioProbe: What, When, and Where Language Models Learn about Sociodemographics
Comments Accepted for publication at EMNLP 2022
Bridging Fairness and Environmental Sustainability in Natural Language Processing
Comments Accepted for publication at EMNLP 2022
Third-Party Aligner for Neural Word Alignments
Comments 12 pages, 4 figures, findings of emnlp 2022
Conciseness: An Overlooked Language Task
Comments EMNLP 2022 Workshop on Text Simplification, Accessibility, and Readability (TSAR)
COPEN: Probing Conceptual Knowledge in Pre-trained Language Models
Comments Accepted by EMNLP 2022
Alleviating Sparsity of Open Knowledge Graphs with Ternary Contrastive Learning
Journal ref EMNLP Findings 2022
Looking at the Overlooked: An Analysis on the Word-Overlap Bias in Natural Language Inference
Comments Accepted at EMNLP 2022
AX-MABSA: A Framework for Extremely Weakly Supervised Multi-label Aspect Based Sentiment Analysis
Comments to be published in EMNLP 2022
Eliciting Knowledge from Large Pre-Trained Models for Unsupervised Knowledge-Grounded Conversation
Comments Accepted to EMNLP 2022 Main Conference. The code is publicly available at https://github.com/lyy1994/PLM_as_KB/tree/main/projects/plm_as_kb
What Language Model to Train if You Have One Million GPU Hours?
Comments Findings of EMNLP 2022
Improving Large-scale Paraphrase Acquisition and Generation
Comments The project webpage is at http://twitter-paraphrase.com/ Accepted at EMNLP 2022
RobustLR: Evaluating Robustness to Logical Perturbation in Deductive Reasoning
Comments Accpeted at EMNLP 2022, code available at https://github.com/INK-USC/RobustLR
When More Data Hurts: A Troubling Quirk in Developing Broad-Coverage Natural Language Understanding Systems
Comments EMNLP 2022
The Curious Case of Control
Comments EMNLP 2022
Exploiting Global and Local Hierarchies for Hierarchical Text Classification
Comments EMNLP 2022
CRIPP-VQA: Counterfactual Reasoning about Implicit Physical Properties via Video Question Answering
Comments Accepted to EMNLP 2022; https://maitreyapatel.com/CRIPP-VQA/
Utilizing Language-Image Pretraining for Efficient and Robust Bilingual Word Alignment
Comments In Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing (EMNLP Findings)
Semantic Segmentation of Legal Documents via Rhetorical Roles
Comments 19 pages, Accepted at Natural Legal Language Processing Workshop, EMNLP 2022
Complex Hyperbolic Knowledge Graph Embeddings with Fast Fourier Transform
Comments Aceepted by the 2022 Conference on Empirical Methods in Natural Language Processing (EMNLP22)
