A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.
Introduces challenges and techniques for creating machine translation for indigenous languages.
An increase in the use of smartphones has laid to the use of the internet and social media platforms. The most commonly used social media platforms are Twitter, Facebook, WhatsApp and Instagram. People are sharing their personal experiences, reviews, feedbacks on the web. The information which is available on the web i…
Amharic is the official language of the Federal Democratic Republic of Ethiopia. There are lots of historic Amharic and Ethiopic handwritten documents addressing various relevant issues including governance, science, religious, social rules, cultures and art works which are very reach indigenous knowledge. The Amharic …
The paper develops a theory of Ehresmann structures in positive characteristic.
We investigate the Brazilian personal income distribution using data from National Household Sample Survey (PNAD), an annual research available by the Brazilian Institute of Geography and Statistics (IBGE). It provides general characteristics of the country's population. Using PNAD data background we also confirm the e…
A cone spherical metric is called irreducible if any developing map of the metric does not have monodromy in . By using the theory of indigenous bundles, we construct on a compact Riemann surface of genus a canonical surjective map from the moduli space of stable extensions of two line bund…
Footfall based biometric system is perhaps the only person identification technique which does not hinder the natural movement of an individual. This is a clear edge over all other biometric systems which require a formidable amount of human intervention and encroach upon an individual's privacy to some extent or the o…
In many developing countries intellectual property infringement and the commerce of pirate goods is an entrepreneurial activity. Digital piracy is very often the only media for having access to music, cinema, books and software. At the same time, bio-prospecting and infringement of indigenous knowledge rights by intern…
Decision tool helps manage biofouling risks for ships in the Baltic Sea.
Deep learning automates biofouling detection in ship hull images.
New ASR system handles multiple languages without needing language-specific encoding.
Study quantifies gender bias in language models across 7 languages.
Paper reviews neurolinguistics and language technologies, emphasizing mutual enrichment.
New technique reduces language biases in large language models.
When a bilingual student learns to solve word problems in math, we expect the student to be able to solve these problem in both languages the student is fluent in,even if the math lessons were only taught in one language. However, current representations in machine learning are language dependent. In this work, we pres…
Paper introduces TrufLL for language model training without labeled data.
System identifies language of transliterated text.
LLMs translate natural language trading intents into correct option strategies using a domain-specific language.
New findings show language models can't simultaneously avoid hallucinations and capture all language richness.
This paper proposes a new method to connect language and physical actions in reinforcement learning.
Julia accelerates machine learning in various fields with balance of efficiency and simplicity.
Neural language modeling (LM) has led to significant improvements in several applications, including Automatic Speech Recognition. However, they typically require large amounts of training data, which is not available for many domains and languages. In this study, we propose a multilingual neural language model archite…
The paper applies math and physics to language models, introducing entropy and geometric concepts.
Multilingual end-to-end (E2E) models have shown great promise in expansion of automatic speech recognition (ASR) coverage of the world's languages. They have shown improvement over monolingual systems, and have simplified training and serving by eliminating language-specific acoustic, pronunciation, and language models…
Benchmark tests spoken language models for infant language learning.
Optimus pre-trains sentences in a latent space for various NLP tasks.
Work shows hallucination detection by LLMs is impossible without expert feedback.
Language models learn from training data and can leak private information.
Large language models predict human sensory judgments across multiple modalities.
New model shows natural language exhibits phase transition similar to physics.
We study unsupervised multilingual alignment, the problem of finding word-to-word translations between multiple languages without using any parallel data. One popular strategy is to reduce multilingual alignment to the much simplified bilingual setting, by picking one of the input languages as the pivot language that w…
This is a lecture note for the course DS-GA 3001 <Natural Language Understanding with Distributed Representation> at the Center for Data Science , New York University in Fall, 2015. As the name of the course suggests, this lecture note introduces readers to a neural network based approach to natural language understand…
Spoken language identification (LID) technologies have improved in recent years from discriminating largely distinct languages to discriminating highly similar languages or even dialects of the same language. One aspect that has been mostly neglected, however, is discrimination of languages for multilingual speakers, d…
We present a TTS neural network that is able to produce speech in multiple languages. The proposed network is able to transfer a voice, which was presented as a sample in a source language, into one of several target languages. Training is done without using matching or parallel data, i.e., without samples of the same …
New approach decouples skill learning and language grounding for autonomous agents.
lamBERT learns language and actions using multimodal BERT.
LORL learns object-centric representations from vision and language.
Recent work has studied the emergence of language among deep reinforcement learning agents that must collaborate to solve a task. Of particular interest are the factors that cause language to be compositional -- i.e., express meaning by combining words which themselves have meaning. Evolutionary linguists have found th…
Transformers improve Finnish language modeling, achieving lower perplexity scores.
VALC provides concept-level interpretations of FLMs, overcoming word-level limitations.
The task of translating between programming languages differs from the challenge of translating natural languages in that programming languages are designed with a far more rigid set of structural and grammatical rules. Previous work has used a tree-to-tree encoder/decoder model to take advantage of the inherent tree s…
Study finds phase transition in context-sensitive language model with short-range interactions.
We propose multi-way, multilingual neural machine translation. The proposed approach enables a single neural translation model to translate between multiple languages, with a number of parameters that grows only linearly with the number of languages. This is made possible by having a single attention mechanism that is …
We present a novel language adaptable spell checking system which detects spelling errors and suggests context sensitive corrections in real-time. We show that our system can be extended to new languages with minimal language-specific processing. Available literature majorly discusses spell checkers for English but the…
Improved robot navigation using multi-head attention for natural language instructions.
Text documents are structured on multiple levels of detail: individual words are related by syntax, but larger units of text are related by discourse structure. Existing language models generally fail to account for discourse structure, but it is crucial if we are to have language models that reward coherence and gener…
Language helps RL agents learn complex relational and causal structures.
The task of determining a speaker's native language based only on his speeches in a second language is known as Native Language Identification or NLI. Due to its increasing applications in various domains of speech signal processing, this has emerged as an important research area in recent times. In this paper we have …