Tech Blog | Featured Capital One Technology

A conversational dataset specifically designed to capture and manage inter-tool dependencies across diverse domains. (NeurIPS)

A novel reward modeling framework that is rubric-agnostic, generalizable and provides reasoned score assignments. (NeurIPS)

Visual reasoning models that achieve SoTA performance using an order of magnitude fewer training samples. (NeurIPS)

A study across models and benchmarks and an alternative test-time scaling approach. (NeurIPS)

An RL proxy task that trains VLMs to localize synthetic hallucinations injected into human-written captions. (NeurIPS)

An evaluation architecture that incorporates reasoning and iterative refinement. (NeurIPS)

An uncertainty measure defined as the cross-entropy between predictive distribution and unknown true distribution. (NeurIPS)

An RL approach that leverages multiple rollouts across paraphrased set to assign group similarity rewards. (NeurIPS)

An efficient, scalable method for generating synthetic pre-training data to enable meta-learning of decision trees. (NeurIPS)