1 citations · 3 across the 12 of their papers we have counts for
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Test-Time Warmup for Multimodal Large Language Models
Nikita Rajaneesh, Thomas Zollo, Richard Zemel
Multimodal Large Language Models (MLLMs) hold great promise for advanced reasoning at the intersection of text and images, yet they have not fully realized this potential. MLLMs ty…
Guiding LLM Decision-Making with Fairness Reward Models
Zara Hall, Melanie Subbiah, Thomas P Zollo +2
Large language models are increasingly used to support high-stakes decisions, potentially influencing who is granted bail or receives a loan. Naive chain-of-thought sampling can im…
QuEst: Enhancing Estimates of Quantile-Based Distributional Measures Using Model Predictions
Zhun Deng, Thomas P Zollo, Benjamin Eyre +3
As machine learning models grow increasingly competent, their predictions can supplement scarce or expensive data in various important domains. In support of this paradigm, algorit…
Confidence Calibration in Vision-Language-Action Models
Thomas P Zollo, Richard Zemel
Trustworthy robot behavior requires not only high levels of task success but also that the robot can reliably quantify how likely it is to succeed. To this end, we present a first-…
Adaptive Elicitation of Latent Information Using Natural Language
Jimmy Wang, Thomas Zollo, Richard Zemel +1
Eliciting information to reduce uncertainty about a latent entity is a critical task in many application domains, e.g., assessing individual student learning outcomes, diagnosing u…