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Found 10 papers, 4 papers with code
To Err Is Human, but Llamas Can Learn It Too
This study explores enhancing grammatical error correction (GEC) through artificial error generation (AEG) using language models (LMs).
True Detective: A Deep Abductive Reasoning Benchmark Undoable for GPT-3 and Challenging for GPT-4
Our work introduces a challenging benchmark for future studies on reasoning in language models and contributes to a better understanding of the limits of LLMs' abilities.
Cross-lingual Similarity of Multilingual Representations Revisited
Related works used indexes like CKA and variants of CCA to measure the similarity of cross-lingual representations in multilingual language models.
Translation Transformers Rediscover Inherent Data Domains
Here we analyze the sentence representations learned by NMT Transformers and show that these explicitly include the information on text domains, even after only seeing the input sentences without domains labels.
Similarity of Sentence Representations in Multilingual LMs: Resolving Conflicting Literature and Case Study of Baltic Languages
However, we observe that Baltic languages do belong to that shared space.
XD: Cross-lingual Knowledge Distillation for Polyglot Sentence Embeddings
Current state-of-the-art results in multilingual natural language inference (NLI) are based on tuning XLM (a pre-trained polyglot language model) separately for each language involved, resulting in multiple models.
Grammatical Error Correction and Style Transfer via Zero-shot Monolingual Translation
Both grammatical error correction and text style transfer can be viewed as monolingual sequence-to-sequence transformation tasks, but the scarcity of directly annotated data for either task makes them unfeasible for most languages.
Phrase-based Unsupervised Machine Translation with Compositional Phrase Embeddings
This paper describes the University of Tartu{'}s submission to the unsupervised machine translation track of WMT18 news translation shared task.
Monolingual and Cross-lingual Zero-shot Style Transfer
We introduce the task of zero-shot style transfer between different languages.
