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Found 11 papers, 6 papers with code
\infty-former: Infinite Memory Transformer
Transformers are unable to model long-term memories effectively, since the amount of computation they need to perform grows with the context length.
EuroLLM: Multilingual Language Models for Europe
The quality of open-weight LLMs has seen significant improvement, yet they remain predominantly focused on English.
Bridging the Gap: A Survey on Integrating (Human) Feedback for Natural Language Generation
Many recent advances in natural language generation have been fueled by training large language models on internet-scale data.
Chunk-based Nearest Neighbor Machine Translation
Semi-parametric models, which augment generation with retrieval, have led to impressive results in language modeling and machine translation, due to their ability to retrieve fine-grained information from a datastore of examples.
Efficient Machine Translation Domain Adaptation
On the other hand, semi-parametric models have been shown to successfully perform domain adaptation by retrieving examples from an in-domain datastore (Khandelwal et al., 2021).
$\infty$-former: Infinite Memory Transformer
Transformers are unable to model long-term memories effectively, since the amount of computation they need to perform grows with the context length.
Ranked #1 on
Dialogue Generation
on CMU-DoG
The GEM Benchmark: Natural Language Generation, its Evaluation and Metrics
We introduce GEM, a living benchmark for natural language Generation (NLG), its Evaluation, and Metrics.
Ranked #1 on
Extreme Summarization
on GEM-XSum
Abstractive Text Summarization
Cross-Lingual Abstractive Summarization
+5
Sparse Text Generation
Current state-of-the-art text generators build on powerful language models such as GPT-2, achieving impressive performance.
Sparse and Structured Visual Attention
Visual attention mechanisms are widely used in multimodal tasks, as visual question answering (VQA).
Joint Learning of Named Entity Recognition and Entity Linking
Named entity recognition (NER) and entity linking (EL) are two fundamentally related tasks, since in order to perform EL, first the mentions to entities have to be detected.
Ranked #12 on
Entity Linking
on AIDA-CoNLL
A deep learning approach for understanding natural language commands for mobile service robots
Using natural language to give instructions to robots is challenging, since natural language understanding is still largely an open problem.
