Llamax: Scaling linguistic horizons of llm by enhancing translation capabilities beyond 100 languages
Large Language Models (LLMs) demonstrate remarkable translation capabilities in high-
resource language tasks, yet their performance in low-resource languages is hindered by …
resource language tasks, yet their performance in low-resource languages is hindered by …
Scaling of search and learning: A roadmap to reproduce o1 from reinforcement learning perspective
OpenAI o1 represents a significant milestone in Artificial Inteiligence, which achieves expert-
level performances on many challanging tasks that require strong reasoning ability. OpenAI …
level performances on many challanging tasks that require strong reasoning ability. OpenAI …
Fairness definitions in language models explained
Language Models (LMs) have demonstrated exceptional performance across various
Natural Language Processing (NLP) tasks. Despite these advancements, LMs can inherit …
Natural Language Processing (NLP) tasks. Despite these advancements, LMs can inherit …
Lumberchunker: Long-form narrative document segmentation
Modern NLP tasks increasingly rely on dense retrieval methods to access up-to-date and
relevant contextual information. We are motivated by the premise that retrieval benefits from …
relevant contextual information. We are motivated by the premise that retrieval benefits from …
xTower: A multilingual LLM for explaining and correcting translation errors
While machine translation (MT) systems are achieving increasingly strong performance on
benchmarks, they often produce translations with errors and anomalies. Understanding …
benchmarks, they often produce translations with errors and anomalies. Understanding …
Emma-500: Enhancing massively multilingual adaptation of large language models
In this work, we introduce EMMA-500, a large-scale multilingual language model continue-
trained on texts across 546 languages designed for enhanced multilingual performance …
trained on texts across 546 languages designed for enhanced multilingual performance …
Beyond English-Centric LLMs: What Language Do Multilingual Language Models Think in?
In this study, we investigate whether non-English-centric LLMs, despite their strong
performance,think'in their respective dominant language: more precisely,think'refers to how …
performance,think'in their respective dominant language: more precisely,think'refers to how …
DiBiMT: A Gold Evaluation Benchmark for Studying Lexical Ambiguity in Machine Translation
Despite the remarkable progress made in the field of Machine Translation (MT), current
systems still struggle when translating ambiguous words, especially when these express …
systems still struggle when translating ambiguous words, especially when these express …
Enhancing translation accuracy of large language models through continual pre-training on parallel data
M Kondo, T Utsuro, M Nagata - arxiv preprint arxiv:2407.03145, 2024 - arxiv.org
In this paper, we propose a two-phase training approach where pre-trained large language
models are continually pre-trained on parallel data and then supervised fine-tuned with a …
models are continually pre-trained on parallel data and then supervised fine-tuned with a …
Prexme! large scale prompt exploration of open source llms for machine translation and summarization evaluation
Large language models (LLMs) have revolutionized the field of NLP. Notably, their in-
context learning capabilities also enable their use as evaluation metrics for natural language …
context learning capabilities also enable their use as evaluation metrics for natural language …