This repository contains the concrete solutions and reproducible scripts produced by the Hyra (Hunyuan Research Agent) across a range of open problems in science, mathematics, engineering, and creative design, with most results surpassing the previous best published values.

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NOASSERTION

Last updated

2026-07-27

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FR-AI / ANALYSIS

Why it is worth attention

It demonstrates the capabilities of a research agent that outperforms prior state-of-the-art on multiple diverse benchmarks (AI4AI, AI4Science, and creative AI4Fun tasks), providing reproducible artifacts that allow the community to verify and build upon its results.

Who it is for

  • AI researchers evaluating autonomous research agents
  • Scientists and mathematicians looking for improved solutions to specific open problems
  • Machine learning engineers interested in reproducible benchmarking
  • Hobbyists exploring AI-generated creative designs (games, music, 3D models)

Use cases

  • Benchmarking the performance of research agents against human-designed baselines
  • Reproducing state-of-the-art results for tasks like autocorrelation constants, packing records, and symbolic forecasting
  • Integrating Hyra's solutions as starting points for further optimization in continuously-updated leaderboards
  • Studying AI-generated creative works such as Reversi bots, music arrangements, and 3D procedural models

Strengths

  • Outperforms previous best published results on 11 out of 12 compared tasks across AI4AI and AI4Science
  • Covers a wide variety of domains (AI research, physics, combinatorics, drug docking, quantum computing, creative design) demonstrating versatility
  • Provides self-contained scripts and final solution artifacts for reproducibility and verification
  • Includes notable creative demos (e.g., AlphaZero-style Reversi bot, music arrangement, 3D models) that showcase the agent's capabilities beyond pure optimization

Considerations

  • Results are frozen as of 2026-07-10; later leaderboard entries may have improved upon Hyra's solutions
  • The repository only contains the output artifacts, not the Hyra agent itself, so users cannot directly run the agent or modify its behavior
  • Some tasks (e.g., AI4Fun) lack quantitative comparisons, making it harder to assess the agent's creative performance objectively

README quick start

Hyra Results

Companion artifacts for Hyra: Hnyuan Research Agent.

This repository collects concrete solutions that Hyra produced across a range of open problems in science, mathematics, engineering, and creative design, released alongside the Hyra launch post. Each folder holds the final solution artifact and, where relevant, the self-contained scripts that reproduce it.

📝 Launch post: hy.tencent.com/research/hyra

Results

Each row compares the best prior published result (Prev best, from the cited system or leaderboard) against Hyra. Arrows mark the better direction (↓ lower is better, ↑ higher is better); the Hyra-winning value is in bold.

TrackTaskMetricPrev bestHyra
AI4AInanochat_autoresearchval BPB ↓0.9109 e0.9015
nanogpt_speedrunwall-clock ↓77.5 s e76.4 s
sol_execbenchscore ↑0.754 e0.771
AI4Scienceautocorrelation_firstC₁ ↓1.502870 a1.502850
autocorrelation_secondR ↑0.962694 b0.962901
erdos_min_overlapC₅ ↓0.380868 b0.380859
sums_diffsC(A) ↑1.14489 b1.21079
packing_recordsrecords brokenn/a f100
smallest_adderparams ↓36 c15
parp1_dockingobjective ↓−9.77 d−10.60
qubit_routingCNOTs added ↓269,037 b258,369
sunspot_symbolicforecast R² ↑0.47 g0.78

Prev-best sources.

  • a TTT-Discover: Learning to Discover at Test Time (arXiv:2601.16175).
  • b SimpleTES: Evaluation-driven Scaling for Scientific Discovery (arXiv:2604.19341).
  • c AdderBoard trained-weights leaderboard (github.com/anadim/AdderBoard).
  • d Olaparib, an approved PARP1 inhibitor (drug baseline).
  • e Recursive: *First Steps Toward Automated AI

Description

Research artifacts from Hyra (/ˈhaɪ.rɑː/)

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