Three-stream network for enriched Action Recognition. - Ivaxi Sheth (CoRR, 2021)

FHIST: A Benchmark for Few-shot Classification of Histological Images. - Fereshteh Shakeri; Malik Boudiaf; Sina Mohammadi; Ivaxi Sheth; Mohammad Havaei; Ismail Ben Ayed; Samira Ebrahimi Kahou (CoRR, 2022)

Latent Variable Models for Bayesian Causal Discovery. - Jithendaraa Subramanian; Yashas Annadani; Ivaxi Sheth; Stefan Bauer; Derek Nowrouzezahrai; Samira Ebrahimi Kahou (CoRR, 2022)

WiCV 2022: The Tenth Women In Computer Vision Workshop. - Doris Antensteiner; Silvia Bucci; Arushi Goel; Marah Halawa; Niveditha Kalavakonda; Tejaswi Kasarla; Miaomiao Liu; Nermin Samet; Ivaxi Sheth (CoRR, 2022)

Learning Latent Structural Causal Models. - Jithendaraa Subramanian; Yashas Annadani; Ivaxi Sheth; Nan Rosemary Ke; Tristan Deleu; Stefan Bauer; Derek Nowrouzezahrai; Samira Ebrahimi Kahou (CoRR, 2022)

Pitfalls of Conditional Batch Normalization for Contextual Multi-Modal Learning. - Ivaxi Sheth; Aamer Abdul Rahman; Mohammad Havaei; Samira Ebrahimi Kahou (CoRR, 2022)

RelationalUNet for Image Segmentation. - Ivaxi Sheth; Pedro H. M. Braga; Shivakanth Sujit; Sahar Dastani; Samira Ebrahimi Kahou (MLMI@MICCAI (1), 2023)

Auxiliary Losses for Learning Generalizable Concept-based Models. - Ivaxi Sheth; Samira Ebrahimi Kahou (NeurIPS, 2023)

Source-free Domain Adaptation Requires Penalized Diversity. - Laya Rafiee Sevyeri; Ivaxi Sheth; Farhood Farahnak; Alexandre See; Samira Ebrahimi Kahou; Thomas Fevens; Mohammad Havaei (CoRR, 2023)

WiCV@CVPR2023: The Eleventh Women In Computer Vision Workshop at the Annual CVPR Conference. - Doris Antensteiner; Marah Halawa; Asra Aslam; Ivaxi Sheth; Sachini Herath; Ziqi Huang; Sunnie S. Y. Kim; Aparna Akula; Xin Wang (CoRR, 2023)

Transparent Anomaly Detection via Concept-based Explanations. - Laya Rafiee Sevyeri; Ivaxi Sheth; Farhood Farahnak; Shirin Abbasinejad Enger (CoRR, 2023)

Survey on AI Ethics: A Socio-technical Perspective. - Dave Mbiazi; Meghana Bhange; Maryam Babaei; Ivaxi Sheth; Patrik Joslin Kenfack (CoRR, 2023)

LLM Task Interference: An Initial Study on the Impact of Task-Switch in Conversational History. - Akash Gupta; Ivaxi Sheth; Vyas Raina; Mark J. F. Gales; Mario Fritz (EMNLP, 2024)

Hypothesizing Missing Causal Variables with LLMs. - Ivaxi Sheth; Sahar Abdelnabi; Mario Fritz (CoRR, 2024)

LLM4GRN: Discovering Causal Gene Regulatory Networks with LLMs - Evaluation through Synthetic Data Generation. - Tejumade Afonja; Ivaxi Sheth; Ruta Binkyte; Waqar Hanif; Thomas Ulas; Matthias Becker 003; Mario Fritz (CoRR, 2024)

MedG-KRP: Medical Graph Knowledge Representation Probing. - Gabriel R. Rosenbaum; Lavender Yao Jiang; Ivaxi Sheth; Jaden Stryker; Anton Alyakin; Daniel Alexander Alber; Nicolas K. Goff; Young Joon Fred Kwon; John Markert; Mustafa Nasir-Moin; Jan Moritz Niehues; Karl L. Sangwon; et al. (CoRR, 2024)

CausalGraph2LLM: Evaluating LLMs for Causal Queries. - Ivaxi Sheth; Bahare Fatemi; Mario Fritz (NAACL (Findings), 2025)

Safety is Essential for Responsible Open-Ended Systems. - Ivaxi Sheth; Jan Wehner; Sahar Abdelnabi; Ruta Binkyte; Mario Fritz (CoRR, 2025)

Causality Is Key to Understand and Balance Multiple Goals in Trustworthy ML and Foundation Models. - Ruta Binkyte; Ivaxi Sheth; Zhijing Jin 001; Mohammad Havaei; Bernhard Schölkopf; Mario Fritz (CoRR, 2025)

ProtocolLLM: RTL Benchmark for SystemVerilog Generation of Communication Protocols. - Arnav Sheth; Ivaxi Sheth; Mario Fritz (CoRR, 2025)