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Databricks KARL Agent Tackles All Enterprise Search Types via RL

Many enterprise RAG pipelines handle one type of search well and fail silently on the rest. Databricks on March 4 released a new agent called KARL, or Knowledge Agents via Reinforcement Learning, that ...

Databricks built a RAG agent it says can handle every kind of enterprise search

Databricks' KARL agent uses reinforcement learning to generalize across six enterprise search behaviors — the problem that breaks most RAG pipelines.
IEEE

ALARM: Safe Reinforcement Learning With Reliable Mimicry for Robust Legged Locomotion

Abstract: Legged robots are supposed to traverse complicated environments, which makes it challenging to design a model-based controller due to their functional complexity. Currently, using deep ...
IEEE

Deep Learning-based Blind Identification of Channel Coding Schemes

Abstract: The signal identification in blind radio frequency environment is gaining increasing importance in intelligent wireless communication systems. In this paper, we present a deep learning based ...
GitHub

Rec-R1: Bridging Generative Large Language Models and User-Centric Recommendation Systems via Reinforcement Learning

REC-R1 is a general framework that bridges generative large language models (LLMs) and recommendation systems via reinforcement learning. Check the paper here.