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Large Language Models

6405 directly classified papers

Papers per year

Papers

ASDOT: Any-Shot Data-to-Text Generation with Pretrained Language Models EMNLP 2022
Language Models Are Poor Learners of Directional Inference EMNLP 2022
ePiC: Employing Proverbs in Context as a Benchmark for Abstract Language Understanding ACL 2022
Plug-and-Play Adaptation for Continuously-updated QA ACL 2022
Extracting Latent Steering Vectors from Pretrained Language Models ACL 2022
Prompt Learning for Domain Adaptation in Task-Oriented Dialogue EMNLP 2022
Towards Few-Shot Identification of Morality Frames using In-Context Learning EMNLP 2022
What GPT Knows About Who is Who ACL 2022
How Much Do Modifications to Transformer Language Models Affect Their Ability to Learn Linguistic Knowledge? ACL 2022
MoEfication: Transformer Feed-forward Layers are Mixtures of Experts ACL 2022
Probing Language Models for Understanding of Temporal Expressions EMNLP 2021
Reconsidering the Past: Optimizing Hidden States in Language Models EMNLP 2021
LMSOC: An Approach for Socially Sensitive Pretraining EMNLP 2021
K-PLUG: Knowledge-injected Pre-trained Language Model for Natural Language Understanding and Generation in E-Commerce EMNLP 2021
LMdiff: A Visual Diff Tool to Compare Language Models EMNLP 2021
How much coffee was consumed during EMNLP 2019? Fermi Problems: A New Reasoning Challenge for AI EMNLP 2021
On the differences between BERT and MT encoder spaces and how to address them in translation tasks ACL 2021
ChineseBERT: Chinese Pretraining Enhanced by Glyph and Pinyin Information ACL 2021
Explaining Relationships Between Scientific Documents ACL 2021
Hi-Transformer: Hierarchical Interactive Transformer for Efficient and Effective Long Document Modeling ACL 2021
Leveraging the Inductive Bias of Large Language Models for Abstract Textual Reasoning NIPS 2021
BASE Layers: Simplifying Training of Large, Sparse Models ICML 2021
How Does BERT Rerank Passages? An Attribution Analysis with Information Bottlenecks EMNLP 2021
Surface Form Competition: Why the Highest Probability Answer Isn’t Always Right EMNLP 2021
Who’s on First?: Probing the Learning and Representation Capabilities of Language Models on Deterministic Closed Domains EMNLP 2021