9 papers
Contemporary AI lacks the imagination to diverge or negate in science
Honglin Bao, Siyang Wu, Xiao Liu +3
Bold claims that AI will accelerate scientific discovery have raced ahead of evidence from working scientists, yet large-scale, scientist-in-the-loop evidence is scarce. Here we mo…
Mapping Overlaps in Benchmarks through Perplexity in the Wild
Siyang Wu, Honglin Bao, Sida Li +2
We introduce benchmark signatures to characterize the capacity demands of LLM benchmarks and their overlaps. Signatures are sets of salient tokens from in-the-wild corpora whose mo…
LLM-as-a-Prophet: Understanding Predictive Intelligence with Prophet Arena
Qingchuan Yang, Simon Mahns, Sida Li +3
Forecasting is not only a fundamental intellectual pursuit but also is of significant importance to societal systems such as finance and economics. With the rapid advances of large…
Prediction-Powered Adaptive Shrinkage Estimation
Sida Li, Nikolaos Ignatiadis
Prediction-Powered Inference (PPI) is a powerful framework for enhancing statistical estimates by combining limited gold-standard data with machine learning (ML) predictions. While…
TDRI: Two-Phase Dialogue Refinement and Co-Adaptation for Interactive Image Generation
Yuheng Feng, Jianhui Wang, Kun Li +5
Although text-to-image generation technologies have made significant advancements, they still face challenges when dealing with ambiguous prompts and aligning outputs with user int…
Enhancing Low-Cost Video Editing with Lightweight Adaptors and Temporal-Aware Inversion
Yangfan He, Sida Li, Jianhui Wang +11
Recent advancements in text-to-image (T2I) generation using diffusion models have enabled cost-effective video-editing applications by leveraging pre-trained models, eliminating th…