IEEE

Curricular Subgoals for Inverse Reinforcement Learning

Abstract: Inverse Reinforcement Learning (IRL) aims to reconstruct the reward function from expert demonstrations to facilitate policy learning, and has demonstrated its remarkable success in ...
The Manila Times

Interview Kickstart's New Advanced Machine Learning and Agentic AI Program 2026 Helps ...

Amid this shift, Interview Kickstart has introduced an advanced machine learning and agentic AI program designed to help ...
GitHub

Demystifying Reinforcement Learning in Agentic Reasoning

An overview of our research on agentic RL. In this work, we systematically investigate three dimensions of agentic RL: data, algorithms, and reasoning modes. Our findings reveal: Real end-to-end ...
GitHub

CapRL: Stimulating Dense Image Caption Capabilities via Reinforcement Learning

We are excited to release the CapRL 2.0 series: CapRL-Qwen3VL-2B and CapRL-Qwen3VL-4B. These models feature fewer parameters while delivering even more powerful captioning performance. Notably, ...
IEEE

Large Language Model for Verilog Generation with Code-Structure-Guided Reinforcement Learning

Abstract: Recent advancements in large language models (LLMs) have sparked significant interest in the automatic generation of Register Transfer Level (RTL) designs, particularly using Verilog.