27 citations · 28 across the 5 of their papers we have counts for
7 papers
DISCOVER: A Solver for Distributional Counterfactual Explanations
Yikai Gu, Lele Cao, Bo Zhao +2
Counterfactual explanations (CE) explain model decisions by identifying input modifications that lead to different predictions. Most existing methods operate at the instance level.…
Self-Supervised Learning of Time Series Representation via Diffusion Process and Imputation-Interpolation-Forecasting Mask
Zineb Senane, Lele Cao, Valentin Leonhard Buchner +6
Time Series Representation Learning (TSRL) focuses on generating informative representations for various Time Series (TS) modeling tasks. Traditional Self-Supervised Learning (SSL)…
Thread: A Logic-Based Data Organization Paradigm for How-To Question Answering with Retrieval Augmented Generation
Kaikai An, Fangkai Yang, Liqun Li +10
Recent advances in retrieval-augmented generation (RAG) have substantially improved question-answering systems, particularly for factoid '5Ws' questions. However, significant chall…
Causality for Tabular Data Synthesis: A High-Order Structure Causal Benchmark Framework
Zineb Senane, Axel Karlsson, Lele Cao +6
Existing evaluations of tabular synthesis models rely primarily on low-order statistics and downstream task performance, leaving multivariate causal relationships that go beyond pa…
GenCeption: Evaluate Vision LLMs with Unlabeled Unimodal Data
Lele Cao, Valentin Buchner, Zineb Senane +1
Multimodal Large Language Models (MLLMs) are typically assessed using expensive annotated multimodal benchmarks, which often lag behind the rapidly evolving demands of MLLM evaluat…
Beyond Gut Feel: Using Time Series Transformers to Find Investment Gems
Lele Cao, Gustaf Halvardsson, Andrew McCornack +2
This paper addresses the growing application of data-driven approaches within the Private Equity (PE) industry, particularly in sourcing investment targets (i.e., companies) for Ve…
Prompt Tuned Embedding Classification for Multi-Label Industry Sector Allocation
Valentin Leonhard Buchner, Lele Cao, Jan-Christoph Kalo +1
Prompt Tuning is emerging as a scalable and cost-effective method to fine-tune Pretrained Language Models (PLMs), which are often referred to as Large Language Models (LLMs). This…