Government
nullnullnullnullnullnullnullnull: A Benchmark for Parsing Ambiguous Questions into Database Queries
In each case, the ambiguity persists even when the database context is provided.
Prior-itizing Privacy: A Bayesian Approach to Setting the Privacy Budget in Differential Privacy
When releasing outputs from confidential data, agencies need to balance the analytical usefulness of the released data with the obligation to protect data subjects'
PrivacyLens: Evaluating Privacy Norm Awareness of Language Models in Action
As language models (LMs) are widely utilized in personalized communication scenarios ( e.g., sending emails, writing social media posts) and endowed with a
Checklist 1. For all authors (a)
A.1 Motivation For what purpose was the dataset created?
MMBench-Video: A Long-Form Multi-Shot Benchmark for Holistic Video Understanding Xinyu Fang
The advent of large vision-language models (L VLMs) has spurred research into their applications in multi-modal contexts, particularly in video understanding.
Compressing Large Language Models using Low Rank and Low Precision Decomposition
Due to the correlated nature of language syntax and semantics learned during training, often, the weight matrices of LLMs exhibit redundancy, which manifests as a low-rank structure. This redundancy suggests the potential for compression without substantial loss in performance.
a13ff984831deea39e6132bafdfdd6d5-Paper-Datasets_and_Benchmarks_Track.pdf
While recent research suggests that current large Vision-Language Models (VLMs) exhibit more reliance on shape, we find them to still be seriously limited in this regard.