# Domain-Specific Question Answering on titanic

Source: [Domain-Specific Question Answering on titanic](<https://www.sota2.com/research/sota/domain-specific-question-answering-on-titanic>)

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

Data updated: 2026-02-26T05:32:50.061Z

Evaluation of domain-specific question answering performance on the Titanic dataset, reporting Accuracy.

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 | domain-specific question answering |
| Dataset (including any stated split) | titanic |
| Metric | Accuracy |
| Unit | PERCENT |
| Direction | Higher is better |
| Results loaded | 5 of 5 |
| 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

- [Accuracy](<https://www.sota2.com/research/sota/domain-specific-question-answering-on-titanic.md?metric=Accuracy>): Higher is better; unit: PERCENT.

## Recorded results

| Method | Accuracy | Result date | Report paper |
| --- | --- | --- | --- |
| Llamdex-MLP | 75.51 | Not recorded | 68fa7c6e1e209131cea8e090 |
| Llamdex-XGBoost | 72.81 | Not recorded | 68fa7c6e1e209131cea8e090 |
| Original LLM | 62.36 | Not recorded | 68fa7c6e1e209131cea8e090 |
| Real Data LoRA | 62.14 | Not recorded | 68fa7c6e1e209131cea8e090 |
| Expert API | 51.46 | Not recorded | 68fa7c6e1e209131cea8e090 |

### Llamdex-MLP

Accuracy: 75.51. Result ID: 699a655a5698665ec4ed8476.

[Reporting paper](<https://www.sota2.com/research/paper/68fa7c6e1e209131cea8e090.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa7c6e1e209131cea8e090.md>)

Recorded evaluation configuration: {"classifier":"MLP"}. This record does not assert independent reproduction.

### Llamdex-XGBoost

Accuracy: 72.81. Result ID: 699a655a5698665ec4ed8475.

[Reporting paper](<https://www.sota2.com/research/paper/68fa7c6e1e209131cea8e090.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa7c6e1e209131cea8e090.md>)

Recorded evaluation configuration: {"classifier":"XGBoost"}. This record does not assert independent reproduction.

### Original LLM

Accuracy: 62.36. Result ID: 699a655a5698665ec4ed8473.

[Reporting paper](<https://www.sota2.com/research/paper/68fa7c6e1e209131cea8e090.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa70d61e209131cea4d909.md>)

[Implementation](<https://github.com/mistralai/mistral-src>)

Recorded evaluation configuration: Not recorded. This record does not assert independent reproduction.

### Real Data LoRA

Accuracy: 62.14. Result ID: 699a655a5698665ec4ed8472.

[Reporting paper](<https://www.sota2.com/research/paper/68fa7c6e1e209131cea8e090.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa6b121e209131cea2bf59.md>)

[Implementation](<https://github.com/microsoft/LoRA>)

Recorded evaluation configuration: {"training\_data":"Real Data"}. This record does not assert independent reproduction.

### Expert API

Accuracy: 51.46. Result ID: 699a655a5698665ec4ed8474.

[Reporting paper](<https://www.sota2.com/research/paper/68fa7c6e1e209131cea8e090.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa6e7d1e209131cea40400.md>)

Recorded evaluation configuration: Not recorded. This record does not assert independent reproduction.

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