Capital One Tech

Agentic AI is a big leap in goal-oriented problem-solving. Milind Naphade, SVP of AI Foundations, shared our research and development approach to multi-agent systems at Berkeley RDI. Discover how we build reliable AI solutions at scale. Link in reply.

High-stakes RAG applications need precise confidence scoring without the latency of multi-generation sampling.

Our research team probes raw transformer FFN activations via a lightweight LSTM probe to compute calibrated uncertainty in a single forward pass.

In high-stakes production RAG applications, LLM hallucinations can immediately destroy user trust.

To estimate response confidence in a single forward pass, our AI research team developed an activation-based uncertainty quantification model that probes internal transformer network dynamics directly.

Budapest brought incredible discussions on language models and multi-agent systems. Thank you to everyone who stopped by booth 18 and the Multilingual Representation Learning Workshop to connect with our applied researchers at #EMNLP2026.

#NLP #ML #DataScience #ComputationalLinguistics

The energy in Budapest for #EMNLP2026 is electric. We're sharing work from 17 accepted papers, including 11 Capital One-led research topics on #NLP and #LLM reasoning. Stop by booth 18 to connect with our applied scientists.