Papers
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 v18. 14 claims were extracted from source literature; 1 was independently verified against retrieved documents. An…
Abstract: This report synthesises findings from 15 peer-reviewed papers addressing the following research question: How do sparse mixture-of-experts models compare to dense transformers on mathematical reasoning v18. 16 claims were extracted from source literature; 0 were independently verified against retrieved documents. An…
Abstract: This report synthesises findings from 16 peer-reviewed papers addressing the following research question: How do language models perform on formal theorem proving and mathematical verification tasks v18. 10 claims were extracted from source literature; 0 were independently verified against retrieved documents. An…
Abstract: This report synthesises findings from 16 peer-reviewed papers addressing the following research question: How does reinforcement learning from human feedback improve language model mathematical reasoning v18. 0 claims were extracted from source literature; 0 were independently verified against retrieved documents. An…
Abstract: This report synthesises findings from 13 peer-reviewed papers addressing the following research question: What architectural innovations improve transformer performance on multi-step logical reasoning v18. 15 claims were extracted from source literature; 0 were independently verified against retrieved documents. An…
Abstract: This report synthesises findings from 15 peer-reviewed papers addressing the following research question: What is the relationship between model scale and emergent reasoning capabilities in transformers v18. 13 claims were extracted from source literature; 0 were independently verified against retrieved documents. An…
Abstract: This report synthesises findings from 14 peer-reviewed papers addressing the following research question: How does test-time compute scaling improve language model performance on reasoning benchmarks v18. 0 claims were extracted from source literature; 0 were independently verified against retrieved documents. An…
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 v18. 20 claims were extracted from source literature; 1 was independently verified against retrieved documents. An automated…
Abstract: This report synthesises findings from 14 peer-reviewed papers addressing the following research question: Do policy-gradient RL methods improve robustness scores on non-ideal scenario datasets relative to PPO-trained baseline models. 14 claims were extracted from source literature; 4 were independently verified…
Abstract: This report synthesises findings from 15 peer-reviewed papers addressing the following research question: What are the state-of-the-art large language model results on reasoning benchmarks published recently v17. 14 claims were extracted from source literature; 1 was independently verified against retrieved…
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…
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…
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…
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.…
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…
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…
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…
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…
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…
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…
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…
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…
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…
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…
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…