2 citations · 4 across the 5 of their papers we have counts for
6 papers
WorkBench Revisited: Workplace Agents Two Years On
Olly Styles, Sam Miller
The best agent on WorkBench in March 2024, GPT-4, completed just 43% of tasks. We revisit the benchmark in June 2026 and find that the best agent to date, Claude Fable 5, now compl…
WorkBench: a Benchmark Dataset for Agents in a Realistic Workplace Setting
Olly Styles, Sam Miller, Patricio Cerda-Mardini +3
We introduce WorkBench: a benchmark dataset for evaluating agents' ability to execute tasks in a workplace setting. WorkBench contains a sandbox environment with five databases, 26…
Joint Learning Architecture for Multiple Object Tracking and Trajectory Forecasting
Oluwafunmilola Kesa, Olly Styles, Victor Sanchez
This paper introduces a joint learning architecture (JLA) for multiple object tracking (MOT) and trajectory forecasting in which the goal is to predict objects' current and future…
Multi-Camera Trajectory Forecasting with Trajectory Tensors
Olly Styles, Tanaya Guha, Victor Sanchez
We introduce the problem of multi-camera trajectory forecasting (MCTF), which involves predicting the trajectory of a moving object across a network of cameras. While multi-camera…
Multi-Camera Trajectory Forecasting: Pedestrian Trajectory Prediction in a Network of Cameras
Olly Styles, Tanaya Guha, Victor Sanchez +1
We introduce the task of multi-camera trajectory forecasting (MCTF), where the future trajectory of an object is predicted in a network of cameras. Prior works consider forecasting…
Multiple Object Forecasting: Predicting Future Object Locations in Diverse Environments
Olly Styles, Tanaya Guha, Victor Sanchez
This paper introduces the problem of multiple object forecasting (MOF), in which the goal is to predict future bounding boxes of tracked objects. In contrast to existing works on o…