4 citations · 4 across the 8 of their papers we have counts for
8 papers
From Critic to Confidence: PPO for Language-Based Quantitative Prediction with Confidence Estimation
Mehak Dhaliwal, Rasta Tadayon, Andong Hua +2
LLMs can perform language-based quantitative prediction from unstructured inputs, but remain susceptible to hallucinations and overconfident errors, making it critical to know not…
TokenSwap: Benchmarking and Reducing the Modality Gap in Multimodal LLMs
Andong Hua, Colton Bishop, Igor Mordatch +5
Multimodal large language models (MLLMs) should exhibit cross-modal consistency, generating consistent responses given semantically equivalent inputs across modalities. However, we…
English is Not All You Need: Systematically Exploring the Role of Multilinguality in LLM Post-Training
Mehak Dhaliwal, Shashwat Chaurasia, Yao Qin +2
Despite the widespread multilingual deployment of large language models, post-training pipelines remain predominantly English-centric, contributing to performance disparities acros…
Flaw or Artifact? Rethinking Prompt Sensitivity in Evaluating LLMs
Andong Hua, Kenan Tang, Chenhe Gu +3
Prompt sensitivity, referring to the phenomenon where paraphrasing (i.e., repeating something written or spoken using different words) leads to significant changes in large languag…
Improving Adversarial Transferability in MLLMs via Dynamic Vision-Language Alignment Attack
Chenhe Gu, Jindong Gu, Andong Hua +1
Multimodal Large Language Models (MLLMs), built upon LLMs, have recently gained attention for their capabilities in image recognition and understanding. However, while MLLMs are vu…
Conflict-Aware Adversarial Training
Zhiyu Xue, Haohan Wang, Yao Qin +1
Adversarial training is the most effective method to obtain adversarial robustness for deep neural networks by directly involving adversarial samples in the training procedure. To…
NutriBench: A Dataset for Evaluating Large Language Models on Nutrition Estimation from Meal Descriptions
Andong Hua, Mehak Preet Dhaliwal, Laya Pullela +2
Accurate nutrition estimation helps people make informed dietary choices and is essential in the prevention of serious health complications. We present NutriBench, the first public…
Initialization Matters for Adversarial Transfer Learning
Andong Hua, Jindong Gu, Zhiyu Xue +3
With the prevalence of the Pretraining-Finetuning paradigm in transfer learning, the robustness of downstream tasks has become a critical concern. In this work, we delve into adver…