Using Segmentation Masks in the ICCV 2019 Learning to Drive Challenge. - Antonia Lovjer; Minsu Yeom; Benedikt D. Schifferer; Iddo Drori (CoRR, 2019)

Accurate Trajectory Prediction for Autonomous Vehicles. - Michael Diodato; Yu Li; Antonia Lovjer; Minsu Yeom; Albert Song; Yiyang Zeng; Abhay Khosla; Benedikt D. Schifferer; Manik Goyal; Iddo Drori (CoRR, 2019)

Tutorial: Feature Engineering for Recommender Systems. - Benedikt Schifferer; Chris Deotte; Even Oldridge (RecSys, 2020)

GPU Accelerated Feature Engineering and Training for Recommender Systems. - Benedikt Schifferer; Gilberto Titericz; Chris Deotte; Christof Henkel; Kazuki Onodera; Jiwei Liu; Bojan Tunguz; Even Oldridge; Gabriel de Souza Pereira Moreira; Ahmet Erdem (RecSys Challenge, 2020)

A Sensorized Multicurved Robot Finger with Data-driven Touch Sensing via Overlapping Light Signals. - Pedro Piacenza; Keith Behrman; Benedikt D. Schifferer; Ioannis Kymissis; Matei T. Ciocarlie (CoRR, 2020)

GPU Accelerated Boosted Trees and Deep Neural Networks for Better Recommender Systems. - Chris Deotte; Bo Liu; Benedikt Schifferer; Gilberto Titericz (RecSys Challenge, 2021)

End-to-End Session-Based Recommendation on GPU. - Gabriel de Souza Pereira Moreira; Sara Rabhi; Ronay Ak; Benedikt Schifferer (RecSys, 2021)

Using Deep Learning to Win the Booking.com WSDM WebTour21 Challenge on Sequential Recommendations. - Benedikt Schifferer; Chris Deotte; Jean-Francois Puget; Gabriel de Souza Pereira Moreira; Gilberto Titericz; Jiwei Liu; Ronay Ak (WebTour@WSDM, 2021)

Robust Temporal Ensembling for Learning with Noisy Labels. - Abel Brown; Benedikt Schifferer; Robert DiPietro (CoRR, 2021)

Reducing the Friction for Building Recommender Systems with Merlin. - Sara Rabhi; Ronay Ak; Marc Romeijn; Gabriel de Souza Pereira Moreira; Benedikt D. Schifferer (KDD, 2022)

Training and Deploying Multi-Stage Recommender Systems. - Ronay Ak; Benedikt Schifferer; Sara Rabhi; Gabriel de Souza Pereira Moreira (RecSys, 2022)

Investigating the effects of incremental training on neural ranking models. - Benedikt Schifferer; Wenzhe Shi; Gabriel de Souza Pereira Moreira; Even Oldridge; Chris Deotte; Gilberto Titericz; Kazuki Onodera; Praveen Dhinwa; Vishal Agrawal; Chris Green (RecSys, 2023)

NV-Retriever: Improving text embedding models with effective hard-negative mining. - Gabriel de Souza Pereira Moreira; Radek Osmulski; Mengyao Xu; Ronay Ak; Benedikt Schifferer; Even Oldridge (CoRR, 2024)

Winning Amazon KDD Cup'24. - Chris Deotte; Ivan Sorokin; Ahmet Erdem; Benedikt Schifferer; Gilberto Titericz; Simon Jégou (CoRR, 2024)

Enhancing Q&A Text Retrieval with Ranking Models: Benchmarking, fine-tuning and deploying Rerankers for RAG. - Gabriel de Souza Pereira Moreira; Ronay Ak; Benedikt Schifferer; Mengyao Xu; Radek Osmulski; Even Oldridge (CoRR, 2024)

AIMO-2 Winning Solution: Building State-of-the-Art Mathematical Reasoning Models with OpenMathReasoning dataset. - Ivan Moshkov; Darragh Hanley; Ivan Sorokin; Shubham Toshniwal; Christof Henkel; Benedikt Schifferer; Wei Du; Igor Gitman (CoRR, 2025)

MIRACL-VISION: A Large, multilingual, visual document retrieval benchmark. - Radek Osmulski; Gabriel de Souza Pereira Moreira; Ronay Ak; Mengyao Xu; Benedikt Schifferer; Even Oldridge (CoRR, 2025)

Llama Nemoretriever Colembed: Top-Performing Text-Image Retrieval Model. - Mengyao Xu; Gabriel de Souza Pereira Moreira; Ronay Ak; Radek Osmulski; Yauhen Babakhin; Zhiding Yu; Benedikt Schifferer; Even Oldridge (CoRR, 2025)