CodeTransOcean: A Comprehensive Multilingual Benchmark for Code Translation
Comments Accepted by Findings of EMNLP 2023
期刊&会议
EMNLP
Conference on Empirical Methods in Natural Language Processing · 会议 · Natural Language Processing
Video-LLaMA: An Instruction-tuned Audio-Visual Language Model for Video Understanding
Comments Accepted by EMNLP 2023's demo track; Code, Pretrained Model, and Dataset: https://github.com/DAMO-NLP-SG/Video-LLaMA
Is a Prestigious Job the same as a Prestigious Country? A Case Study on Multilingual Sentence Embeddings and European Countries
Comments 10 pages, 1 figure; Findings of EMNLP 2023, camera-ready
Image Manipulation via Multi-Hop Instructions -- A New Dataset and Weakly-Supervised Neuro-Symbolic Approach
Comments EMNLP 2023 (long paper, main conference)
Coarse-to-Fine Contrastive Learning in Image-Text-Graph Space for Improved Vision-Language Compositionality
Comments EMNLP 2023 (long paper, main conference)
Asking Clarification Questions to Handle Ambiguity in Open-Domain QA
Comments 15 pages, 4 figures, accepted to EMNLP 2023 Findings
A Diachronic Analysis of Paradigm Shifts in NLP Research: When, How, and Why?
Comments accepted at EMNLP 2023
Mitigating Data Imbalance and Representation Degeneration in Multilingual Machine Translation
Comments Accepted to Findings of EMNLP 2023, add statistical significance tests. code available at https://github.com/lavine-lmu/Bi-ACL
TELeR: A General Taxonomy of LLM Prompts for Benchmarking Complex Tasks
Comments Accepted to EMNLP 2023
Incorporating Structured Representations into Pretrained Vision & Language Models Using Scene Graphs
Comments EMNLP 2023
API-Bank: A Comprehensive Benchmark for Tool-Augmented LLMs
Comments EMNLP 2023
Knowledge Distillation $\approx$ Label Smoothing: Fact or Fallacy?
Comments EMNLP 2023
Open Domain Multi-document Summarization: A Comprehensive Study of Model Brittleness under Retrieval
Comments Accepted to EMNLP Findings 2023
What to Read in a Contract? Party-Specific Summarization of Legal Obligations, Entitlements, and Prohibitions
Comments EMNLP 2023
CR-COPEC: Causal Rationale of Corporate Performance Changes to Learn from Financial Reports
Comments Accepted in Findings of EMNLP 2023
Practical Computational Power of Linear Transformers and Their Recurrent and Self-Referential Extensions
Comments Accepted to EMNLP 2023 (short paper)
Instruct and Extract: Instruction Tuning for On-Demand Information Extraction
Comments EMNLP 2023
Dissecting In-Context Learning of Translations in GPTs
Comments EMNLP Findings (+ Minor Updates over Camera-Ready)
This is not a Dataset: A Large Negation Benchmark to Challenge Large Language Models
Comments Accepted in the The 2023 Conference on Empirical Methods in Natural Language Processing (EMNLP 2023)
Contrastive Learning-based Sentence Encoders Implicitly Weight Informative Words
Comments 16 pages, 6 figures, accepted to EMNLP 2023 Findings (short paper)
In-Context Learning Creates Task Vectors
Comments Accepted at Findings of EMNLP 2023
Is Probing All You Need? Indicator Tasks as an Alternative to Probing Embedding Spaces
Comments Findings of EMNLP 2023
Do Stochastic Parrots have Feelings Too? Improving Neural Detection of Synthetic Text via Emotion Recognition
Comments Accepted to Findings of EMNLP 2023 (long paper). Camera ready version
Using Artificial French Data to Understand the Emergence of Gender Bias in Transformer Language Models
Comments Accepted at EMNLP'23
A Diffusion Weighted Graph Framework for New Intent Discovery
Comments EMNLP 2023 Main
Unnatural language processing: How do language models handle machine-generated prompts?
Comments Findings of EMNLP 2023 Camera-Ready
DALE: Generative Data Augmentation for Low-Resource Legal NLP
Comments Accepted to EMNLP 2023 Main Conference. Code: https://github.com/Sreyan88/DALE
Random Entity Quantization for Parameter-Efficient Compositional Knowledge Graph Representation
Comments Accepted to EMNLP 2023
BLESS: Benchmarking Large Language Models on Sentence Simplification
Comments This paper has been accepted to EMNLP 2023 as a main long paper. 9 pages, 7 figures
Learning From Free-Text Human Feedback -- Collect New Datasets Or Extend Existing Ones?
Comments Accepted to be presented at EMNLP 2023
