18 citations · 25 across the 5 of their papers we have counts for
6 papers
Auditing Future-Memory Use in Point-in-Time Language Agents
Rongtian Ye
Point-in-time (PIT) agents can recall post-cutoff facts even when their external evidence respects a historical cutoff. We examine whether this access predicts evidence gathering i…
ChartDiff: A Large-Scale Benchmark for Comprehending Pairs of Charts
Rongtian Ye
Charts are central to analytical reasoning, yet existing benchmarks for chart understanding focus almost exclusively on single-chart interpretation rather than comparative reasonin…
HAL: Improved Text-Image Matching by Mitigating Visual Semantic Hubs
Fangyu Liu, Rongtian Ye, Xun Wang +1
The hubness problem widely exists in high-dimensional embedding space and is a fundamental source of error for cross-modal matching tasks. In this work, we study the emergence of h…
A Strong and Robust Baseline for Text-Image Matching
Fangyu Liu, Rongtian Ye
We review the current schemes of text-image matching models and propose improvements for both training and inference. First, we empirically show limitations of two popular loss (su…
3D Depthwise Convolution: Reducing Model Parameters in 3D Vision Tasks
Rongtian Ye, Fangyu Liu, Liqiang Zhang
Standard 3D convolution operations require much larger amounts of memory and computation cost than 2D convolution operations. The fact has hindered the development of deep neural n…
3DCNN-DQN-RNN: A Deep Reinforcement Learning Framework for Semantic Parsing of Large-scale 3D Point Clouds
Fangyu Liu, Shuaipeng Li, Liqiang Zhang +4
Semantic parsing of large-scale 3D point clouds is an important research topic in computer vision and remote sensing fields. Most existing approaches utilize hand-crafted features…