activity
20202026
most citedA unified framework for dataset shift diagnostics

15 citations · 24 across the 18 of their papers we have counts for

collaborators

21 papers

cs.AI2026

Rich Insights from Cheap Signals: Efficient Evaluations via Tensor Factorization

Felipe Maia Polo, Aida Nematzadeh, Virginia Aglietti +2

Moving beyond evaluations that collapse performance across heterogeneous prompts toward fine-grained evaluation at the prompt level, or within relatively homogeneous subsets, is ne…

stat.AP2025

A Latent Variable Framework for Scaling Laws in Large Language Models

Peiyao Cai, Chengyu Cui, Felipe Maia Polo +6

We propose a statistical framework built on latent variable modeling for scaling laws of large language models (LLMs). Our work is motivated by the rapid emergence of numerous new…

cs.CL2025

COMET-poly: Machine Translation Metric Grounded in Other Candidates

Maike Züfle, Vilém Zouhar, Tu Anh Dinh +3

Automated metrics for machine translation attempt to replicate human judgment. Unlike humans, who often assess a translation in the context of multiple alternatives, these metrics…

cs.LG2025

Bridging Human and LLM Judgments: Understanding and Narrowing the Gap

Felipe Maia Polo, Xinhe Wang, Mikhail Yurochkin +3

Large language models are increasingly used as judges (LLM-as-a-judge) to evaluate model outputs at scale, but their assessments often diverge systematically from human judgments.…

cs.IR2025

Personalized Image Generation for Recommendations Beyond Catalogs

Gabriel Patron, Zhiwei Xu, Ishan Kapnadak +1

Personalization is central to human-AI interaction, yet current diffusion-based image generation systems remain largely insensitive to user diversity. Existing attempts to address…

stat.ML2025

CARROT: A Cost Aware Rate Optimal Router

Seamus Somerstep, Felipe Maia Polo, Allysson Flavio Melo de Oliveira +5

With the rapid growth in the number of Large Language Models (LLMs), there has been a recent interest in LLM routing, or directing queries to the cheapest LLM that can deliver a su…