[MIT] RLCR: Teaching AI models to say "I'm not sure"

<!-- SC_OFF --><div class="md"><p>A wrong answer in a chatbot is frustrating.</p> <p>A wrong action from an AI system is different.</p> <p>The dangerous part is not just that it

<!-- SC_OFF --><div class="md"><p>I grew up around people who were confidently incorrect, so when someone provides answers that are provably false without equivocating, it causes

A new training method improves the reliability of AI confidence estimates without sacrificing performance, addressing a root cause of hallucination in reasoning models.

<table> <tr><td> <a href="https://www.reddit.com/r/singularity/comments/1srx4i1/new_llm_position_bias_benchmark_does_an_llm_keep/"> <img alt="New LLM Position Bias Benchmark: does

<!-- SC_OFF --><div class="md"><p>I am trying to understand the current consensus and legal landscape regarding how public data and developer contributions are being utilized by

<!-- SC_OFF --><div class="md"><p>I've been working on creating an AI-generated image detector and everything so called &quot;state-of-the-art&quot; in academic studies failed

<!-- SC_OFF --><div class="md"><p>First, the models are strictly censored during the reasoning process. I remember seeing a document when OpenAI released a new model (I don't

<!-- SC_OFF --><div class="md"><p>AI images used to have tells. Broken text, messed up hands, faces that couldn’t survive a single edit.</p> <p>That’s basicaly gone now. So what