Language models (LMs) often exhibit undesirable text generation behavior...
Language models (LMs) often struggle to pay enough attention to the inpu...
One of the ultimate quests of question answering (QA) is to deploy a sys...
Large language models (LLMs) are increasingly adopted for knowledge-inte...
Large language models are typically trained densely: all parameters are
...
Fine-tuning a language model on a new domain is standard practice for do...
We introduce REPLUG, a retrieval-augmented language modeling framework t...
Large language models can perform new tasks in a zero-shot fashion, give...
Existing language models (LMs) predict tokens with a softmax over a fini...
Recent multimodal models such as DALL-E and CM3 have achieved remarkable...
Image captioning aims to describe an image with a natural language sente...
We introduce RoMQA, the first benchmark for robust, multi-evidence,
mult...
We introduce kNN-Prompt, a simple and effective technique to use k-neare...
Short textual descriptions of entities provide summaries of their key
at...
Cross-lingual Entity Linking (XEL) grounds mentions of entities that app...
Much research effort has been put to multilingual knowledge graph (KG)
e...
We consider the compilation of a binary neural network's decision functi...
Contextualized word embedding models, such as ELMo, generate meaningful
...
Recent studies have shown that word embeddings exhibit gender bias inher...
Bilingual word embeddings, which representlexicons of different language...
Embedding models for deterministic Knowledge Graphs (KG) have been
exten...