activity
20242026
most citedHumanity's Last Exam

18 citations · 18 across the 3 of their papers we have counts for

collaborators

18 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.LG202618 cited

Humanity's Last Exam

Long Phan, Alice Gatti, Ziwen Han +1144

Benchmarks are important tools for tracking the rapid advancements in large language model (LLM) capabilities. However, benchmarks are not keeping pace in difficulty: LLMs now achi…

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.LG2025

A Sober Look at Progress in Language Model Reasoning: Pitfalls and Paths to Reproducibility

Andreas Hochlehnert, Hardik Bhatnagar, Vishaal Udandarao +3

Reasoning has emerged as the next major frontier for language models (LMs), with rapid advances from both academic and industrial labs. However, this progress often outpaces method…

cs.LG2025

ONEBench to Test Them All: Sample-Level Benchmarking Over Open-Ended Capabilities

Adhiraj Ghosh, Sebastian Dziadzio, Ameya Prabhu +3

Traditional fixed test sets fall short in evaluating open-ended capabilities of foundation models. To address this, we propose ONEBench(OpeN-Ended Benchmarking), a new testing para…