RLTasksby ulam.ai
Models / OpenAI

OpenAI / MODEL EVIDENCE

GPT-4o React

2 benchmarks · 11 observations · 2 sources

Scores at a glance

2 benchmarks · large dot: GPT-4o React; small dots: closest models where reported

DiscoveryWorld ↗59%
5659

GPT-4o / ReACT · DiscoveryWorld · Average (Easy) · Procedure · GPT-4o agent scaffolds ↗

8 more reported results

38% · GPT-4o / ReACT · DiscoveryWorld · Average (Easy) · Task completion · GPT-4o agent scaffolds · DISCOVERYWORLD: A Virtual Environment for Developing and Evaluating Automated Scientific Discovery Agents ↗

25% · GPT-4o / ReACT · DiscoveryWorld · Average (Easy) · Explanatory knowledge · GPT-4o agent scaffolds · DISCOVERYWORLD: A Virtual Environment for Developing and Evaluating Automated Scientific Discovery Agents ↗

63% · GPT-4o / ReACT · DiscoveryWorld · Average (Normal) · Procedure · GPT-4o agent scaffolds · DISCOVERYWORLD: A Virtual Environment for Developing and Evaluating Automated Scientific Discovery Agents ↗

18% · GPT-4o / ReACT · DiscoveryWorld · Average (Normal) · Task completion · GPT-4o agent scaffolds · DISCOVERYWORLD: A Virtual Environment for Developing and Evaluating Automated Scientific Discovery Agents ↗

14% · GPT-4o / ReACT · DiscoveryWorld · Average (Normal) · Explanatory knowledge · GPT-4o agent scaffolds · DISCOVERYWORLD: A Virtual Environment for Developing and Evaluating Automated Scientific Discovery Agents ↗

63% · GPT-4o / ReACT · DiscoveryWorld · Average (Challenge) · Procedure · GPT-4o agent scaffolds · DISCOVERYWORLD: A Virtual Environment for Developing and Evaluating Automated Scientific Discovery Agents ↗

18% · GPT-4o / ReACT · DiscoveryWorld · Average (Challenge) · Task completion · GPT-4o agent scaffolds · DISCOVERYWORLD: A Virtual Environment for Developing and Evaluating Automated Scientific Discovery Agents ↗

10% · GPT-4o / ReACT · DiscoveryWorld · Average (Challenge) · Explanatory knowledge · GPT-4o agent scaffolds · DISCOVERYWORLD: A Virtual Environment for Developing and Evaluating Automated Scientific Discovery Agents ↗

Closest models by score

Similar positions on shared benchmark leaderboards. Smaller gaps are closer.

There are not enough shared scored settings to identify close comparisons reliably.

Filter comparisons to this model →

Sources

Every plotted observation links to its evaluation. Reported configurations, benchmark versions and task subsets can differ; similarity describes shared scores, not training lift.

  1. DISCOVERYWORLD: A Virtual Environment for Developing and Evaluating Automated Scientific Discovery Agents — published result table ↗

    Jansen, Peter, Côté, Marc-Alexandre, Khot, Tushar, Bransom, Erin, Mishra, Bhavana Dalvi, Majumder, Bodhisattwa Prasad et al. · 2024

    All 8 authors

    Jansen, Peter, Côté, Marc-Alexandre, Khot, Tushar, Bransom, Erin, Mishra, Bhavana Dalvi, Majumder, Bodhisattwa Prasad, Tafjord, Oyvind, Clark, Peter

  2. Are large language models superhuman chemists? — published result table ↗

    Adrian Mirza, Nawaf Alampara, Sreekanth Kunchapu, Martiño Ríos-García, Benedict Emoekabu, Aswanth Krishnan et al. · 2024

    All 35 authors

    Adrian Mirza, Nawaf Alampara, Sreekanth Kunchapu, Martiño Ríos-García, Benedict Emoekabu, Aswanth Krishnan, Tanya Gupta, Mara Schilling-Wilhelmi, Macjonathan Okereke, Anagha Aneesh, Amir Mohammad Elahi, Mehrdad Asgari, Juliane Eberhardt, Hani M. Elbeheiry, María Victoria Gil, Maximilian Greiner, Caroline T. Holick, Christina Glaubitz, Tim Hoffmann, Abdelrahman Ibrahim, Lea C. Klepsch, Yannik Köster, Fabian Alexander Kreth, Jakob Meyer, Santiago Miret, Jan Matthias Peschel, Michael Ringleb, Nicole Roesner, Johanna Schreiber, Ulrich S. Schubert, Leanne M. Stafast, Dinga Wonanke, Michael Pieler, Philippe Schwaller, Kevin Maik Jablonka

Names used in source tables

GPT-4o / ReACT · GPT-4o React