5 papers
Fast Inference via Hierarchical Speculative Decoding
Clara Mohri, Haim Kaplan, Tal Schuster +2
Transformer language models generate text autoregressively, making inference latency proportional to the number of tokens generated. Speculative decoding reduces this latency witho…
Towards an AI-Augmented Textbook
LearnLM Team, Google, : +34
Textbooks are a cornerstone of education, but they have a fundamental limitation: they are a one-size-fits-all medium. Any new material or alternative representation requires arduo…
Teaching Models to Improve on Tape
Liat Bezalel, Eyal Orgad, Amir Globerson
Large Language Models (LLMs) often struggle when prompted to generate content under specific constraints. However, in such cases it is often easy to check whether these constraints…
Do LLMs have Consistent Values?
Naama Rozen, Liat Bezalel, Gal Elidan +2
Large Language Models (LLM) technology is constantly improving towards human-like dialogue. Values are a basic driving force underlying human behavior, but little research has been…
TACT: Advancing Complex Aggregative Reasoning with Information Extraction Tools
Avi Caciularu, Alon Jacovi, Eyal Ben-David +5
Large Language Models (LLMs) often do not perform well on queries that require the aggregation of information across texts. To better evaluate this setting and facilitate modeling…