collaborators

5 papers

cs.CV2026

ZeroBench: An Impossible Visual Benchmark for Contemporary Large Multimodal Models

Jonathan Roberts, Mohammad Reza Taesiri, Ansh Sharma +31

Large Multimodal Models (LMMs) exhibit shortfalls when interpreting images and, by some measures, have poorer spatial cognition than young children or animals. Despite this, they a…

cs.CL2026

How Long Is a Piece of String? A Brief Empirical Analysis of Tokenizers

Jonathan Roberts, Kai Han, Samuel Albanie

Frontier LLMs are increasingly utilised across academia, society and industry. A commonly used unit for comparing models, their inputs and outputs, and estimating inference pricing…

cs.CV2025

GRAB: A Challenging GRaph Analysis Benchmark for Large Multimodal Models

Jonathan Roberts, Kai Han, Samuel Albanie

Large multimodal models (LMMs) have exhibited proficiencies across many visual tasks. Although numerous well-known benchmarks exist to evaluate model performance, they increasingly…

cs.CL2025

GAMEBoT: Transparent Assessment of LLM Reasoning in Games

Wenye Lin, Jonathan Roberts, Yunhan Yang +3

Large Language Models (LLMs) are increasingly deployed in real-world applications that demand complex reasoning. To track progress, robust benchmarks are required to evaluate their…

cs.CL2025

Needle Threading: Can LLMs Follow Threads through Near-Million-Scale Haystacks?

Jonathan Roberts, Kai Han, Samuel Albanie

As the context limits of Large Language Models (LLMs) increase, the range of possible applications and downstream functions broadens. In many real-world tasks, decisions depend on…