Publications

Foundational research advancing the state of the art in AI.

Capital One’s Applied AI research

publications

M4-RAG: A multimodal RAG

A massive-scale benchmark for evaluating retrieval-augmented VQA across languages and modalities. (CVPR)

publications

VLMs are confused tourists

A novel cultural adversarial robustness suite designed to assess VLMs’ stability against perturbed geographical cues. (CVPR)

publications

Uncertainty as feature gaps

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

publications

MR3: Multilingual rubric-agnostic reward reasoning models

A multilingual, rubric-agnostic reward reasoning model achieving the broadest language coverage in reward modeling to date. (ICLR)

publications

DynaGuard: A dynamic guardian model

A suite of dynamic guardian models offering novel flexibility by evaluating text based on user-defined policies. (ICLR)

publications

Distillation versus contrastive learning

An empirical comparison of contrastive learning and knowledge distillation. (AACL)

publications

LLM reasoning for cold-start item recommendation

Novel reasoning strategies designed for cold-start item recommendations within the Netflix domain. (WWW)

publications

DF-RAG: Enhancing RAG for question answering

A pipeline that dynamically adapts the level of diversity for each query at test time without requiring prior information. (EACL)

publications

Deconstructing instruction-following

A modular framework that uses a dynamically generated dataset to evaluate the capability of Large Language Models. (EACL)