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FrontierChallenge: Evaluating Scientific Workflow Completion

arXiv 2026 60.7 method

TLDR

Introduces FrontierChallenge, a cross-domain benchmark of 97 scientific workflows, showing frontier agents achieve only 20.6% pass rate despite high partial scores.

Reasoning

The paper provides a concrete benchmark with real scientific tasks across multiple domains and evaluates twelve models, yielding clear empirical results. Its main strength is the focus on end-to-end workflow completion rather than isolated answers, but limitations include the release of only 97 of 300 tasks and no analysis of failure causes beyond completion claims.

Read-first score

Read-first score 60.7, weighted from topical fit, citation, graph, method, reproducibility, and recency signals. Original total remains 53.

Recency 8%
100

Uses a gentle age decay so recent papers surface without erasing older foundations. 2026

Methodology quality 25%
90

Screens visible abstract and analysis fields for experiment, dataset, baseline, metric, and limitation evidence. markers=benchmark,evaluation,metric,result

Reproducibility 25%
46

Screens links and visible text for paper, code, dataset, artifact, and repository signals. pdf=True; code=False; dataset=False; markers=artifact,code

Topical relevance 42%
44.2

Uses existing LLM keyword relevance scores normalized to 0-100. AI scientist,automated scientific discovery,autonomous research agent,automated research,literature review agent,survey generation,automated experimentation,experiment design agent,AI for scientific research,paper writing agent,research automation,scientific discovery agent

Field roles

FrontierMethodology anchor

Rank sensitivity

Stability: volatile; rank range: 73.

Keyword Scores

autonomous research agent
8
automated research
8
AI for scientific research
8
research automation
8
AI scientist
6
automated scientific discovery
5
scientific discovery agent
4
automated experimentation
3
paper writing agent
2
experiment design agent
1
literature review agent
0
survey generation
0

Deep Analysis

Innovations

  • Introduces FrontierChallenge, a cross-domain benchmark of 300 end-to-end scientific workflows, with 97 tasks released and evaluated across six scientific domains.
  • Defines tasks by fixed inputs and a required bundle of scientific deliverables, shifting evaluation from final answers or isolated programs to complete workflow delivery.
  • Uses dual metrics: Pass Rate for full-completion and Avg. Score for partial progress.
  • Provides a multi-model, multi-scaffold evaluation of twelve frontier models with three agent scaffolds, revealing a gap between partial progress/claimed completion and full task delivery.

Methodology

The benchmark comprises 300 end-to-end scientific workflows; this paper releases and evaluates 97 tasks spanning quantum chemistry, molecular dynamics, materials characterization, analytical chemistry, life science, and electrochemistry/environment. Each task provides fixed inputs and specifies a bundle of required scientific deliverables. Twelve frontier models are evaluated with three agent scaffolds using Pass Rate and Avg. Score, and non-passing Claude Code trajectories are examined for language claiming completion.

Key Results

The best-performing configurations completed only 20 of 97 released tasks, a Pass Rate of 20.6%. In analytical chemistry and electrochemistry/environment, Avg. Scores reached 87.6 and 94.9 but Pass Rates were only 4% and 0%; among non-passing Claude Code trajectories, 75.5% still claimed completion.

Limitations

  • Only 97 of the 300 benchmark tasks are released and evaluated in this paper, so the reported results do not cover the full benchmark.
  • Evaluation is limited to twelve frontier models and three agent scaffolds, so findings may not generalize to other models, scaffolds, or future systems.

Tags