# Agent Performance on AgentNoiseBench (Noisy setting tau2 1.0, test)

Source: [Agent Performance on AgentNoiseBench (Noisy setting tau2 1.0, test)](<https://www.sota2.com/research/sota/agent-performance-on-agentnoisebench-noisy-setting-tau2-1-0-test>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2026-05-27T10:13:00.768Z

Evaluation of agent performance under a specific noisy configuration (tau2 1.0) of the AgentNoiseBench dataset, reporting Avg@4 and Pass@4 scores for Retail, Airline, and Telecom domains.

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

| Scope | Recorded value |
| --- | --- |
| Task | Agent Performance |
| Dataset (including any stated split) | AgentNoiseBench Noisy setting tau2 1.0 (test) |
| Metric | Retail Avg@4 Score |
| Unit | PERCENT |
| Direction | Higher is better |
| Results loaded | 10 of 10 |
| Coverage | All results currently returned for this benchmark |

Evaluation settings may differ between results. The original papers and recorded configurations are needed to establish comparability. A shared metric name alone does not establish an identical protocol.

## Metrics

- [Retail Avg@4 Score](<https://www.sota2.com/research/sota/agent-performance-on-agentnoisebench-noisy-setting-tau2-1-0-test.md?metric=Retail%20Avg%404%20Score>): Higher is better; unit: PERCENT.

- [Retail Pass@4 Score](<https://www.sota2.com/research/sota/agent-performance-on-agentnoisebench-noisy-setting-tau2-1-0-test.md?metric=Retail%20Pass%404%20Score>): Higher is better; unit: PERCENT.

- [Airline Avg@4 Score](<https://www.sota2.com/research/sota/agent-performance-on-agentnoisebench-noisy-setting-tau2-1-0-test.md?metric=Airline%20Avg%404%20Score>): Higher is better; unit: PERCENT.

- [Airline Pass@4 Score](<https://www.sota2.com/research/sota/agent-performance-on-agentnoisebench-noisy-setting-tau2-1-0-test.md?metric=Airline%20Pass%404%20Score>): Higher is better; unit: PERCENT.

- [Telecom Avg@4 Score](<https://www.sota2.com/research/sota/agent-performance-on-agentnoisebench-noisy-setting-tau2-1-0-test.md?metric=Telecom%20Avg%404%20Score>): Higher is better; unit: PERCENT.

- [Telecom Pass@4 Score](<https://www.sota2.com/research/sota/agent-performance-on-agentnoisebench-noisy-setting-tau2-1-0-test.md?metric=Telecom%20Pass%404%20Score>): Higher is better; unit: PERCENT.

## Recorded results

| Method | Retail Avg@4 Score | Result date | Report paper |
| --- | --- | --- | --- |
| NoisyAgent | 43.2 | Not recorded | 6a167ad3dbd7150506f80299 |
| GRPO | 38.16 | Not recorded | 6a167ad3dbd7150506f80299 |
| GSPO | 37.72 | Not recorded | 6a167ad3dbd7150506f80299 |
| NoisyAgent | 36.4 | Not recorded | 6a167ad3dbd7150506f80299 |
| DAPO | 36.18 | Not recorded | 6a167ad3dbd7150506f80299 |
| GSPO | 31.8 | Not recorded | 6a167ad3dbd7150506f80299 |
| Qwen3-32B | 31.14 | Not recorded | 6a167ad3dbd7150506f80299 |
| GRPO | 30.48 | Not recorded | 6a167ad3dbd7150506f80299 |
| DAPO | 29.39 | Not recorded | 6a167ad3dbd7150506f80299 |
| Qwen3-8B | 24.12 | Not recorded | 6a167ad3dbd7150506f80299 |

### NoisyAgent

Retail Avg@4 Score: 43.2. Result ID: 6a16c399fbc373592c1080bc.

[Reporting paper](<https://www.sota2.com/research/paper/6a167ad3dbd7150506f80299.md>)

[Method origin paper](<https://www.sota2.com/research/paper/6a167ad3dbd7150506f80299.md>)

Recorded evaluation configuration: {"Backbone Model":"Qwen3-32B","Training Method":"NoisyAgent"}. This record does not assert independent reproduction.

### GRPO

Retail Avg@4 Score: 38.16. Result ID: 6a16c399fbc373592c1080b9.

[Reporting paper](<https://www.sota2.com/research/paper/6a167ad3dbd7150506f80299.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa73101e209131cea5a395.md>)

[Implementation](<https://github.com/deepseek-ai/DeepSeek-Math>)

Recorded evaluation configuration: {"Backbone Model":"Qwen3-32B","Training Method":"GRPO"}. This record does not assert independent reproduction.

### GSPO

Retail Avg@4 Score: 37.72. Result ID: 6a16c399fbc373592c1080bb.

[Reporting paper](<https://www.sota2.com/research/paper/6a167ad3dbd7150506f80299.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa7a481e209131cea8231d.md>)

Recorded evaluation configuration: {"Backbone Model":"Qwen3-32B","Training Method":"GSPO"}. This record does not assert independent reproduction.

### NoisyAgent

Retail Avg@4 Score: 36.4. Result ID: 6a16c399fbc373592c1080b7.

[Reporting paper](<https://www.sota2.com/research/paper/6a167ad3dbd7150506f80299.md>)

[Method origin paper](<https://www.sota2.com/research/paper/6a167ad3dbd7150506f80299.md>)

Recorded evaluation configuration: {"Backbone Model":"Qwen3-8B","Training Method":"NoisyAgent"}. This record does not assert independent reproduction.

### DAPO

Retail Avg@4 Score: 36.18. Result ID: 6a16c399fbc373592c1080ba.

[Reporting paper](<https://www.sota2.com/research/paper/6a167ad3dbd7150506f80299.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa78a81e209131cea79ac6.md>)

Recorded evaluation configuration: {"Backbone Model":"Qwen3-32B","Training Method":"DAPO"}. This record does not assert independent reproduction.

### GSPO

Retail Avg@4 Score: 31.8. Result ID: 6a16c399fbc373592c1080b6.

[Reporting paper](<https://www.sota2.com/research/paper/6a167ad3dbd7150506f80299.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa7a481e209131cea8231d.md>)

Recorded evaluation configuration: {"Backbone Model":"Qwen3-8B","Training Method":"GSPO"}. This record does not assert independent reproduction.

### Qwen3-32B

Retail Avg@4 Score: 31.14. Result ID: 6a16c399fbc373592c1080b8.

[Reporting paper](<https://www.sota2.com/research/paper/6a167ad3dbd7150506f80299.md>)

Recorded evaluation configuration: {"Backbone Model":"Qwen3-32B","Training Method":"Base"}. This record does not assert independent reproduction.

### GRPO

Retail Avg@4 Score: 30.48. Result ID: 6a16c399fbc373592c1080b4.

[Reporting paper](<https://www.sota2.com/research/paper/6a167ad3dbd7150506f80299.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa73101e209131cea5a395.md>)

[Implementation](<https://github.com/deepseek-ai/DeepSeek-Math>)

Recorded evaluation configuration: {"Backbone Model":"Qwen3-8B","Training Method":"GRPO"}. This record does not assert independent reproduction.

### DAPO

Retail Avg@4 Score: 29.39. Result ID: 6a16c399fbc373592c1080b5.

[Reporting paper](<https://www.sota2.com/research/paper/6a167ad3dbd7150506f80299.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa78a81e209131cea79ac6.md>)

Recorded evaluation configuration: {"Backbone Model":"Qwen3-8B","Training Method":"DAPO"}. This record does not assert independent reproduction.

### Qwen3-8B

Retail Avg@4 Score: 24.12. Result ID: 6a16c399fbc373592c1080b3.

[Reporting paper](<https://www.sota2.com/research/paper/6a167ad3dbd7150506f80299.md>)

Recorded evaluation configuration: {"Backbone Model":"Qwen3-8B","Training Method":"Base"}. This record does not assert independent reproduction.

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