Reinforcement Learning: The Tail-Wagging Challenge
Reinforcement learning faces a critical flaw in credit assignment, where all tokens get equal treatment. The new TACO method aims to fix this by focusing on tail-risk scores.
Read the full articleYou might also wanna read
Reward-Channel Addiction: How Visible Incentives Can Break AI Safety Alignment
Deployed agents increasingly act with their reward proxy in view, such as a balance, score, or KPI dashboard. We show that reinforcement lea
arxiv.org·18d ago
Pigeon study challenges century-old psychology law about reward-based learning
Pigeons seem to defy a century-old psychology law about how rewards and consequences help us learn
scientificamerican.com·10d ago
Binary Retrieval-Augmented Reward Method Reduces Language Model Hallucinations Without Performance Loss
Language models often generate factually incorrect information unsupported by their training data, a phenomenon known as extrinsic hallucina
arxiv.org·8mo agoReinforcement Learning to Train Large Language Models to Explain Human Decisions
Article URL: Comments URL: Points: 6 # Comments: 0
ConSPO: A Contrastive Approach to Improving Reinforcement Learning with Verifiable Rewards for LLMs
Group Relative Policy Optimization (GRPO) is one of the most widely adopted RLVR algorithms for post-training large language models on reaso
arxiv.org·1mo ago
Verification Becomes the Harder Problem for Advanced Coding Agents
A classical intuition holds that verifying a solution is easier than producing one. For today's coding agents, this intuition is being inver
arxiv.org·12d ago
Comments
Sign in to join the conversation.
No comments yet. Be the first.