Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context
G Team, P Georgiev, VI Lei, R Burnell, L Bai… - arXiv preprint arXiv …, 2024 - arxiv.org
In this report, we introduce the Gemini 1.5 family of models, representing the next generation
of highly compute-efficient multimodal models capable of recalling and reasoning over fine …
of highly compute-efficient multimodal models capable of recalling and reasoning over fine …
Foundational challenges in assuring alignment and safety of large language models
This work identifies 18 foundational challenges in assuring the alignment and safety of large
language models (LLMs). These challenges are organized into three different categories …
language models (LLMs). These challenges are organized into three different categories …
RULER: What's the Real Context Size of Your Long-Context Language Models?
The needle-in-a-haystack (NIAH) test, which examines the ability to retrieve a piece of
information (the" needle") from long distractor texts (the" haystack"), has been widely …
information (the" needle") from long distractor texts (the" haystack"), has been widely …
Large language models can help boost food production, but be mindful of their risks
D De Clercq, E Nehring, H Mayne… - Frontiers in Artificial …, 2024 - frontiersin.org
Coverage of ChatGPT-style large language models (LLMs) in the media has focused on
their eye-catching achievements, including solving advanced mathematical problems and …
their eye-catching achievements, including solving advanced mathematical problems and …
Hire a linguist!: Learning endangered languages in LLMs with in-context linguistic descriptions
How can large language models (LLMs) process and translate endangered languages?
Many languages lack a large corpus to train a decent LLM; therefore existing LLMs rarely …
Many languages lack a large corpus to train a decent LLM; therefore existing LLMs rarely …
Proof of thought: Neurosymbolic program synthesis allows robust and interpretable reasoning
Large Language Models (LLMs) have revolutionized natural language processing, yet they
struggle with inconsistent reasoning, particularly in novel domains and complex logical …
struggle with inconsistent reasoning, particularly in novel domains and complex logical …
Hire a Linguist!: Learning Endangered Languages with In-Context Linguistic Descriptions
How can large language models (LLMs) process and translate endangered languages?
Many languages lack a large corpus to train a decent LLM; therefore existing LLMs rarely …
Many languages lack a large corpus to train a decent LLM; therefore existing LLMs rarely …
Machine Translation for Ge'ez Language
AK Wassie - arXiv preprint arXiv:2311.14530, 2023 - arxiv.org
Machine translation (MT) for low-resource languages such as Ge'ez, an ancient language
that is no longer spoken in daily life, faces challenges such as out-of-vocabulary words …
that is no longer spoken in daily life, faces challenges such as out-of-vocabulary words …
Natural Language Processing RELIES on Linguistics
Large Language Models (LLMs) have become capable of generating highly fluent text in
certain languages, without modules specially designed to capture grammar or semantic …
certain languages, without modules specially designed to capture grammar or semantic …
Evaluating Large Language Models along Dimensions of Language Variation: A Systematik Invesdigatiom uv Cross-lingual Generalization
While large language models exhibit certain cross-lingual generalization capabilities, they
suffer from performance degradation (PD) on unseen closely-related languages (CRLs) and …
suffer from performance degradation (PD) on unseen closely-related languages (CRLs) and …