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Found 6 papers, 2 papers with code
Decomposing Label Space, Format and Discrimination: Rethinking How LLMs Respond and Solve Tasks via In-Context Learning
Counter-intuitively, we find that the demonstrations have a marginal impact on provoking discriminative knowledge of language models.
Backdoor Attacks on Dense Passage Retrievers for Disseminating Misinformation
To achieve this, we propose a perilous backdoor attack triggered by grammar errors in dense passage retrieval.
Adapt in Contexts: Retrieval-Augmented Domain Adaptation via In-Context Learning
Large language models (LLMs) have showcased their capability with few-shot inference known as in-context learning.
Domain Confused Contrastive Learning for Unsupervised Domain Adaptation
In this work, we study Unsupervised Domain Adaptation (UDA) in a challenging self-supervised approach.
Generative Imagination Elevates Machine Translation
Given a sentence in a source language, whether depicting the visual scene helps translation into a target language?
Ranked #7 on
Multimodal Machine Translation
on Multi30K
On the Robustness of Language Encoders against Grammatical Errors
We conduct a thorough study to diagnose the behaviors of pre-trained language encoders (ELMo, BERT, and RoBERTa) when confronted with natural grammatical errors.
