10 citations · 11 across the 4 of their papers we have counts for
4 papers · 1 filter
Measure Less, Know More: Self-Supervised Test-Time Feature Acquisition
Eeshaan Jain, Linus Bleistein, Bart Deplancke +1
Recent progress in multimodal, high-dimensional learning has enabled foundation models to process heterogeneous, large-scale data. However, at test time, acquiring all features or…
MTBBench: A Multimodal Sequential Clinical Decision-Making Benchmark in Oncology
Kiril Vasilev, Alexandre Misrahi, Eeshaan Jain +5
Multimodal Large Language Models (LLMs) hold promise for biomedical reasoning, but current benchmarks fail to capture the complexity of real-world clinical workflows. Existing eval…
Efficient Data Subset Selection to Generalize Training Across Models: Transductive and Inductive Networks
Eeshaan Jain, Tushar Nandy, Gaurav Aggarwal +3
Existing subset selection methods for efficient learning predominantly employ discrete combinatorial and model-specific approaches which lack generalizability. For an unseen archit…
Graph Edit Distance with General Costs Using Neural Set Divergence
Eeshaan Jain, Indradyumna Roy, Saswat Meher +2
Graph Edit Distance (GED) measures the (dis-)similarity between two given graphs, in terms of the minimum-cost edit sequence that transforms one graph to the other. However, the ex…