Marktechpost

MARCH 26, 2024

In conclusion, the LLM2LLM framework offers a robust solution to the critical challenge of data scarcity. By harnessing the power of one LLM to improve another, it demonstrates a novel, efficient pathway to fine-tune models for specific tasks with limited initial data. Similarly, on the CaseHOLD dataset, there was a 32.6%

Large Language Models 131

Large Language Models Data Scarcity Natural Language Processing LLM 131

Marktechpost

AUGUST 3, 2023

First, they proposed an LLM-based approach to generate a music captioning dataset, LP-MusicCaps. Second, they proposed a systemic evaluation scheme for music captions generated by LLMs. The researchers compared this LLM-based caption generator with template-based methods (tag concatenation, prompt template ) and K2C augmentation.

Data Scarcity 52

Data Scarcity Large Language Models BERT Natural Language Processing 52

Marktechpost

FEBRUARY 29, 2024

Data scarcity in low-resource languages can be mitigated using word-to-word translations from high-resource languages. However, bilingual lexicons typically need more overlap with task data, leading to inadequate translation coverage. Check out the Paper.

Artificial Intelligence 99

Artificial Intelligence Artificial Intelligence Data Scarcity NLP 99

Marktechpost

AUGUST 5, 2024

LLMs are suggested to complete the SiST task because of their enormous success with machine and spoken translation. Starting with the read-write policy, which requires LLM only to offer partial translation for input speech, integrating LLM into the SiST takes work.

Data Scarcity 114

Data Scarcity LLM Natural Language Processing NLP 114

Marktechpost

AUGUST 12, 2024

The Mutation strategy prompts the LLM to modify vulnerable code samples, ensuring that the changes do not alter the code’s original functionality. The Injection strategy involves retrieving similar vulnerable and clean code samples, with the LLM injecting the vulnerable logic into the clean code to create new samples.

Large Language Models 107

Large Language Models Data Scarcity Software Engineer LLM 107

Marktechpost

JULY 8, 2024

The performance of the preference-trained model was evaluated against several state-of-the-art multilingual LLMs. win rate against Aya 23 8B, the current leading multilingual LLM in its parameter class. The results were impressive, with the preference-trained model achieving a 54.4% Additionally, the model showed a 69.5%

Data Scarcity 130

Data Scarcity Large Language Models Natural Language Processing NLP 130

Marktechpost

JANUARY 28, 2025

Augmentation Augmentation plays a central role in fine-tuning by extending the capabilities of LLMs by incorporating external data or techniques. For example, augmenting an LLM with legal terminology can significantly improve its performance in drafting contracts or summarizing case law.

Large Language Models 112

Large Language Models LLM Data Scarcity Explainability 112

AWS Machine Learning Blog

FEBRUARY 12, 2025

You can create synthetic training data using a larger language model and use it to fine-tune a smaller model, which has the benefit of a quicker turnaround time. In this post, we explore how to use Amazon Bedrock to generate synthetic training data to fine-tune an LLM. The following chart summarizes the judges decisions.

LLM 74

LLM Generative AI Deep Learning Data Scarcity 74

Marktechpost

SEPTEMBER 2, 2023

They optimize the LVLM using synthesized anomalous visual-textual data and incorporating IAD expertise. Direct training using IAD data, however, needs to be improved. Data scarcity is the first. It alleviates the constraint of LLM’s restricted ability to generate text outputs.

Data Scarcity 120

Data Scarcity Large Language Models Natural Language Processing LLM 120

Marktechpost

FEBRUARY 27, 2024

For instance, BloomberGPT excels in finance with private financial data spanning 40 years. Collaborative training on decentralized personal data, without direct sharing, emerges as a critical approach to support the development of modern LLMs amid data scarcity and privacy concerns.

Large Language Models 101

Large Language Models Machine Learning Data Scarcity Algorithm 101

Marktechpost

DECEMBER 10, 2024

Traditionally, addressing these challenges involved relying on human-labeled data or leveraging LLMs as judges to verify trajectories. While LLM-based solutions have shown promise, they face significant limitations, including sensitivity to input prompts, inconsistent outputs from API-based models, and high operational costs.

Machine Learning 85

Machine Learning Data Scarcity LLM Large Language Models 85

Marktechpost

SEPTEMBER 8, 2024

The development of Cantonese-specific LLMs faces significant challenges due to limited research and resources. Most existing Cantonese LLM technology remains closed-source, hindering widespread progress in the field. The scarcity of training data and benchmarks for Cantonese LLMs further complicates development efforts.

Large Language Models 102

Large Language Models NLP Neural Network Data Scarcity 102

Marktechpost

MARCH 4, 2025

Supervised fine-tuning, reinforcement learning techniques like PPO, and alternative methods like DPO and IPO have been explored for refining LLM outputs based on user preferences. The approach generates over a million structured synthetic preferences to address data scarcity.

Machine Learning 65

Machine Learning Data Scarcity LLM OpenAI 65

TheSequence

APRIL 14, 2024

We review UC Berkeley’s Gorilla LLM which is fine-tuned for tool learning and the Microsoft TaskWeaver framework. AlphaGeometry combines a geometry symbolic model with an LLM used mostly for exploring possible solutions to a given problem. Can we expand the AlphaGeometry approach to mainstream use cases?

Data Scarcity 52

Data Scarcity LLM Neural Network ML 52

John Snow Labs

OCTOBER 16, 2023

Strategy and Data: Non-top-performers highlight strategizing (24%), talent availability (21%), and data scarcity (18%) as their leading challenges. Large language models (LLMs) are a powerful new technology with the potential to revolutionize many industries. Unstructured.IO

Large Language Models 52

Large Language Models NLP Metadata Data Scarcity 52

Marktechpost

SEPTEMBER 28, 2024

It also uses a symmetric local alignment module to focus on detailed features and a parameter-efficient fine-tuning approach to enhance pre-trained LLMs with medical knowledge. This allows the framework to overcome data scarcity and perform better on mammography tasks.

Data Scarcity 56

Data Scarcity LLM ML Computer Vision 56

Marktechpost

JANUARY 8, 2025

While deep learning’s scaling effects have driven advancements in AI, particularly in LLMs like GPT, further scaling during training faces limitations due to data scarcity and computational constraints. Also,dont forget to follow us on Twitter and join our Telegram Channel and LinkedIn Gr oup.

Data Scarcity 46

Data Scarcity LLM Deep Learning AI 46

Allen AI

NOVEMBER 28, 2023

2) Next, we use the LLM to generate a short narrative based on the sentence form commonsense knowledge. Madeleine and coach) using the LLM. (3) 3) Finally, with the conversation participants and narrative as input, we prompt the LLM to generate a full, multi-turn conversation. Madeleine moves a step closer to the goal.” (2)

Data Scarcity 52

Data Scarcity Large Language Models LLM AI 52

Allen AI

DECEMBER 4, 2023

Bottom) REFLEX adds a “rational” layer above the LLM layer, in which a belief graph is constructed (by iteratively querying the LLM, up/down arrows), containing relevant model-believed facts (white/grey = believed T/F) and their inferential relationships.

Natural Language Processing 52

Natural Language Processing Large Language Models Data Scarcity NLP 52

Unite.AI

MARCH 13, 2024

Here are some notable examples: Legal Domain Law LLM Assistant SaulLM-7B Equall.ai Codex-Med : Exploring GPT-3 for Healthcare QA While not introducing a new LLM, the Codex-Med study explored the effectiveness of GPT-3.5 models, specifically Codex and InstructGPT, in answering and reasoning about real-world medical questions.

Natural Language Processing 201

Natural Language Processing Large Language Models Data Scarcity LLM 201

AWS Machine Learning Blog

DECEMBER 4, 2024

About the NVIDIA Nemotron model family At the forefront of the NVIDIA Nemotron model family is Nemotron-4, as stated by NVIDIA, it is a powerful multilingual large language model (LLM) trained on an impressive 8 trillion text tokens, specifically optimized for English, multilingual, and coding tasks.

Machine Learning 93

Machine Learning Large Language Models Auto-complete Data Scarcity 93

Marktechpost

SEPTEMBER 15, 2024

This surprising trend highlights the continued relevance of SLMs and raises important questions about their role in the LLM era, a topic previously overlooked in research. This study examines the role of SMs in the LLM era from two perspectives: collaboration with LLMs and competition against them.

BERT 117

BERT LLM Large Language Models Categorization 117

AWS Machine Learning Blog

DECEMBER 18, 2024

With a vision to build a large language model (LLM) trained on Italian data, Fastweb embarked on a journey to make this powerful AI capability available to third parties. To achieve this, the team built an extensive Italian language dataset by combining public sources and acquiring licensed data from publishers and media companies.

Large Language Models 90

Large Language Models Data Scarcity LLM Generative AI 90