13 citations · 16 across the 8 of their papers we have counts for
3 papers · 1 filter
Adaptive Margin RLHF via Preference over Preferences
Yaswanth Chittepu, Prasann Singhal, Greg Durrett +1
Margin-based optimization is fundamental to improving generalization and robustness in classification tasks. In the context of reward model learning from preferences within Reinfor…
Assessing Robustness to Spurious Correlations in Post-Training Language Models
Julia Shuieh, Prasann Singhal, Apaar Shanker +3
Supervised and preference-based fine-tuning techniques have become popular for aligning large language models (LLMs) with user intent and correctness criteria. However, real-world…
ChartMuseum: Testing Visual Reasoning Capabilities of Large Vision-Language Models
Liyan Tang, Grace Kim, Xinyu Zhao +12
Chart understanding presents a unique challenge for large vision-language models (LVLMs), as it requires the integration of sophisticated textual and visual reasoning capabilities.…