Reconstructing unmeasured causal drivers of complex time series from observed response data represents a fundamental challenge across diverse scientific domains. Latent variables, including genetic ...

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 ...

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 ...

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 ...

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 ...

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 ...

Smartphones are essential tools in dAIly life. However, the complexity of tasks on mobile devices often leads to frustration and inefficiency. Navigating applications and managing multi-step processes ...

Modern NLP applications often demand multi-step reasoning, interaction with external tools, and the ability to adapt dynamically to user queries. Haystack Agents, an innovative feature of the Haystack ...