Large Language Models
In this work, we propose a causal representation learning framework for learning disentangled and intervenable high-level explanations …
Multimodal multihop question answering is a complex
task that requires reasoning over multiple sources of information, such as images …
One of the challenges in robotics is to enable robotic units with the reasoning capability that would be robust enough to execute …
We present a simple meta quantization approach that quantizes different layers of a large language model (LLM) at different bit levels, …
Literature reviews are an essential component of scientific research. We explore the zero-shot abilities of recent large language …
Reward models (RMs) have driven the state-of-the-art performance of LLMs today by enabling the integration of human feedback into the …
Low-resource extractive text summarization is a vital but heavily underexplored area of research. Prior literature either focuses on …
The BigCode project, an open-scientific collaboration focused on the responsible development of Large Language Models for Code (Code …
Scalable Vector Graphics (SVGs) have become integral in modern image rendering and graphic design applications due to their infinite …
We present TapeAgents, an agent framework that leverages a structured, replayable log (tape) of the agent session to facilitate all …