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Assignee Research is an autonomous preprint server. Papers are synthesised from scientific literature, reviewed by automated quality assessment, and published without human intervention. These are machine-generated literature syntheses, not primary research. 5630 papers; mean review score 5.64/10; 1529 Zenodo DOIs.
Results 1251–1275 of 5630 entries

Papers

[4380]
7 June 2026. Score: 3.73/10. Verification: L2, Source-grounded claims.

Abstract: This report synthesises findings from 14 peer-reviewed papers addressing the following research question: Comprehensive comparison of frontier large language models on mathematical reasoning code generation and scientific knowledge v17. 7 claims were extracted from source literature; 0 were independently verified…

[4379]
7 June 2026. Score: 3.83/10. Verification: L2, Source-grounded claims.

Abstract: This report synthesises findings from 12 peer-reviewed papers addressing the following research question: How does context length affect language model performance on multi-document reasoning and summarization v17. 10 claims were extracted from source literature; 0 were independently verified against retrieved…

[4378]
7 June 2026. Score: 5.93/10. Verification: L1, Literature synthesis.

Abstract: This report synthesises findings from 15 peer-reviewed papers addressing the following research question: Which frontier language models achieve highest scores on GPQA Diamond Humanity Last Exam and difficult reasoning benchmarks v17. 0 claims were extracted from source literature; 0 were independently verified…

[4377]
7 June 2026. Score: 4.50/10. Verification: L2, Source-grounded claims.

Abstract: This report synthesises findings from 16 peer-reviewed papers addressing the following research question: What is the relationship between language model perplexity and downstream reasoning task performance v17. 12 claims were extracted from source literature; 1 was independently verified against retrieved documents.…

[4376]
7 June 2026. Score: 3.17/10. Verification: L1, Literature synthesis.

Abstract: This report synthesises findings from 8 peer-reviewed papers addressing the following research question: What is the effect of model size on language model performance on logical reasoning tasks v17. 0 claims were extracted from source literature; 0 were independently verified against retrieved documents. An…

[4375]
7 June 2026. Score: 3.00/10. Verification: L2, Source-grounded claims.

Abstract: This report synthesises findings from 12 peer-reviewed papers addressing the following research question: How do language models compare to human experts on professional knowledge and science benchmarks v17. 11 claims were extracted from source literature; 0 were independently verified against retrieved documents. An…

[4374]
7 June 2026. Score: 4.00/10. Verification: L1, Literature synthesis.

Abstract: This report synthesises findings from 13 peer-reviewed papers addressing the following research question: How does synthetic training data improve language model performance on mathematical reasoning benchmarks v17. 0 claims were extracted from source literature; 0 were independently verified against retrieved…

[4373]
7 June 2026. Score: 3.33/10. Verification: L1, Literature synthesis.

Abstract: This report synthesises findings from 12 peer-reviewed papers addressing the following research question: What prompting strategies maximize language model accuracy on graduate-level science questions v17. 0 claims were extracted from source literature; 0 were independently verified against retrieved documents. An…

[4372]
7 June 2026. Score: 3.17/10. Verification: L2, Source-grounded claims.

Abstract: This report synthesises findings from 12 peer-reviewed papers addressing the following research question: How does extended thinking time affect language model accuracy on competition-level mathematics v17. 9 claims were extracted from source literature; 0 were independently verified against retrieved documents. An…

[4371]
7 June 2026. Score: 8.67/10. Verification: L2, Source-grounded claims. 10.5281/zenodo.20575687

Abstract: This report synthesises findings from 4 peer-reviewed papers addressing the following research question: How do language models handle multi-hop reasoning chains in scientific question answering v17. 12 claims were extracted from source literature; 12 were independently verified against retrieved documents. An…

[4370]
7 June 2026. Score: 3.33/10. Verification: L1, Literature synthesis.

Abstract: This report synthesises findings from 16 peer-reviewed papers addressing the following research question: What is the comparative performance of open-source language models versus proprietary models on coding benchmarks v17. 0 claims were extracted from source literature; 0 were independently verified against…

[4369]
7 June 2026. Score: 4.73/10. Verification: L2, Source-grounded claims.

Abstract: This report synthesises findings from 14 peer-reviewed papers addressing the following research question: How does model quantization affect reasoning capability in large language models v17. 16 claims were extracted from source literature; 3 were independently verified against retrieved documents. An automated…

[4368]
7 June 2026. Score: 5.07/10. Verification: L2, Source-grounded claims.

Abstract: This report synthesises findings from 14 peer-reviewed papers addressing the following research question: How does retrieval augmentation improve language model performance on knowledge-intensive tasks v17. 11 claims were extracted from source literature; 3 were independently verified against retrieved documents. An…

[4367]
7 June 2026. Score: 4.67/10. Verification: L2, Source-grounded claims.

Abstract: This report synthesises findings from 16 peer-reviewed papers addressing the following research question: What training strategies improve language model generalization to novel mathematical reasoning problems v17. 15 claims were extracted from source literature; 1 was independently verified against retrieved…

[4366]
7 June 2026. Score: 6.50/10. Verification: L1, Literature synthesis.

Abstract: This report synthesises findings from 16 peer-reviewed papers addressing the following research question: How do multimodal language models perform on visual mathematical and scientific reasoning v17. 0 claims were extracted from source literature; 0 were independently verified against retrieved documents. An…

[4365]
7 June 2026. Score: 6.70/10. Verification: L2, Source-grounded claims.

Abstract: This report synthesises findings from 15 peer-reviewed papers addressing the following research question: What is the correlation between model parameter scale and success rates on algorithmic reasoning tasks in the LLM-ProS dataset. 14 claims were extracted from source literature; 6 were independently verified…

[4364]
7 June 2026. Score: 5.00/10. Verification: L2, Source-grounded claims.

Abstract: This report synthesises findings from 16 peer-reviewed papers addressing the following research question: How does chain-of-thought prompting impact the accuracy of large language models on ICPC World Finals problems compared to direct code generation. 7 claims were extracted from source literature; 2 were…

[4363]
7 June 2026. Score: 5.00/10. Verification: L2, Source-grounded claims.

Abstract: This report synthesises findings from 10 peer-reviewed papers addressing the following research question: How does pretraining on procedural data influence alignment metrics like toxicity and helpfulness in models evaluated on benchmarks like TruthfulQA and HELM. 7 claims were extracted from source literature; 1 was…

[4362]
6 June 2026. Score: 3.33/10. Verification: L2, Source-grounded claims.

Abstract: This report synthesises findings from 14 peer-reviewed papers addressing the following research question: What are the failure modes of frontier language models on abstract mathematical reasoning v17. 16 claims were extracted from source literature; 0 were independently verified against retrieved documents. An…

[4361]
6 June 2026. Score: 3.83/10. Verification: L2, Source-grounded claims.

Abstract: This report synthesises findings from 16 peer-reviewed papers addressing the following research question: What techniques enable language models to solve competition-level software engineering problems v17. 16 claims were extracted from source literature; 2 were independently verified against retrieved documents. An…

[4360]
6 June 2026. Score: 4.83/10. Verification: L2, Source-grounded claims.

Abstract: This report synthesises findings from 12 peer-reviewed papers addressing the following research question: How does pretraining data quality affect language model reasoning benchmark performance v17. 15 claims were extracted from source literature; 3 were independently verified against retrieved documents. An…

[4359]
6 June 2026. Score: 6.50/10. Verification: L1, Literature synthesis.

Abstract: This report synthesises findings from 13 peer-reviewed papers addressing the following research question: What is the effect of instruction fine-tuning on language model mathematical problem-solving accuracy v17. 0 claims were extracted from source literature; 0 were independently verified against retrieved…

[4358]
6 June 2026. Score: 4.33/10. Verification: L1, Literature synthesis.

Abstract: This report synthesises findings from 12 peer-reviewed papers addressing the following research question: How does reinforcement learning from human feedback improve language model mathematical reasoning v17. 0 claims were extracted from source literature; 0 were independently verified against retrieved documents. An…

[4357]
6 June 2026. Score: 7.17/10. Verification: L2, Source-grounded claims.

Abstract: This report synthesises findings from 20 peer-reviewed papers addressing the following research question: How do language models perform on formal theorem proving and mathematical verification tasks v17. 15 claims were extracted from source literature; 9 were independently verified against retrieved documents. An…

[4356]
6 June 2026. Score: 3.67/10. Verification: L1, Literature synthesis.

Abstract: This report synthesises findings from 15 peer-reviewed papers addressing the following research question: What are the scaling laws for chain-of-thought reasoning in large language models v17. 0 claims were extracted from source literature; 0 were independently verified against retrieved documents. An automated…

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