As large language models (LLMs) continue to evolve, understanding their ability to reflect on and articulate their learned behaviors has become an important aspect of research. Such capabilities, if ...

Tokenization, the process of breaking text into smaller units, has long been a fundamental step in natural language processing (NLP). However, it presents several challenges. Tokenizer-based language ...

Text-to-speech (TTS) technology has emerged as a critical tool for bridging the gap between human and machine interaction. The demand for lifelike, emotionally resonant, and linguistically versatile ...

The design and deployment of modern RLMs pose a lot of challenges. They are expensive to develop, have proprietary restrictions, and have complex architectures that limit their access. Moreover, the ...

Comprehension and management of large-scale software repositories is a recurring problem in contemporary software development. Although current tools shine when summarizing small code entities such as ...

Lexicon-based embeddings are one of the good alternatives to dense embeddings, yet they face numerous challenges that restrain their wider adoption. One key problem is tokenization redundancy, whereby ...

Aligning large language models (LLMs) with human values is essential as these models become central to various societal functions. A significant challenge arises when model parameters cannot be ...

Out of the various methods employed in document search systems, “retrieve and rank” has gained quite some popularity. Using this method, the results of a retrieval model are re-ordered according to a ...

Now, let’s look into their latest research on ZKLoRA. In this research, the Bagel Research Team focuses on enabling efficient and secure verification of Low-Rank Adaptation (LoRA) updates for LLMs in ...

It can significantly enhance LLMs’ problem-solving capabilities by guiding them to think more deeply about complex problems and effectively utilize inference-time computation. Prior research has ...

The study of autonomous agents powered by large language models (LLMs) has shown great promise in enhancing human productivity. These agents are designed to assist in various tasks such as coding, ...

The advent of advanced AI models has led to innovations in how machines process information, interact with humans, and execute tasks in real-world settings. Two emerging pioneering approaches are ...