2025-10-30
Researchers at Meta FAIR and the University of Edinburgh have developed a new technique that can predict the correctness of a large language model's (LLM) reasoning and even intervene to fix its mistakes. Called Circuit-based Reasoning Verification (CRV), the method looks inside an LLM to monitor its internal “reasoning circuits” and detect signs of computational errors as the model solves a problem.
Their findings show that CRV can detect reasoning errors in LLMs with high accuracy by building and observing a computational graph from the model's internal activations. In a key breakthrough, the researchers also demonstrated they can use this deep insight to apply targeted interventions that correct a model’s faulty reason [...]
2025-11-17
AI engineers often chase performance by scaling up LLM parameters and data, but the trend toward smaller, more efficient, and better-focused models has accelerated. The Phi-4 fine-tuning methodology [...]
2025-12-02
Researchers at MiroMind AI and several Chinese universities have released OpenMMReasoner, a new training framework that improves the capabilities of language models in multimodal reasoning.The framewo [...]
2025-10-31
Some of the most successful creators on Facebook aren't names you'd ever recognize. In fact, many of their pages don't have a face or recognizable persona attached. Instead, they run pa [...]
2025-01-15
The Federal Trade Commission (FTC) has filed a suit against John Deere, accusing it of “unfair” practices that force farmers to pay higher-than-average repair costs. The federal organization, alon [...]
2025-11-06
Even as concern and skepticism grows over U.S. AI startup OpenAI's buildout strategy and high spending commitments, Chinese open source AI providers are escalating their competition and one has e [...]