Papers
Abstract: This report synthesises findings from 4 peer-reviewed papers addressing the following research question: How does reinforcement learning from human feedback improve language model mathematical reasoning v12. 8 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 perform on formal theorem proving and mathematical verification tasks v12. 7 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: What is the relationship between model scale and emergent reasoning capabilities in transformers v12. 11 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: What architectural innovations improve transformer performance on multi-step logical reasoning v12. 10 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 does test-time compute scaling improve language model performance on reasoning benchmarks v12. 0 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: What are the scaling laws for chain-of-thought reasoning in large language models v12. 8 claims were extracted from source literature; 0 were independently verified against retrieved documents. An automated…
Abstract: This report synthesises findings from 4 peer-reviewed papers addressing the following research question: Comprehensive comparison of frontier large language models on mathematical reasoning code generation and scientific knowledge v11. 10 claims were extracted from source literature; 0 were independently verified…
Abstract: This report synthesises findings from 4 peer-reviewed papers addressing the following research question: What are the state-of-the-art large language model results on reasoning benchmarks published recently v11. 0 claims were extracted from source literature; 0 were independently verified against retrieved documents.…
Abstract: This report synthesises findings from 4 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 v11. 8 claims were extracted from source literature; 0 were independently verified…
Abstract: This report synthesises findings from 4 peer-reviewed papers addressing the following research question: What are the limitations of current language model evaluation benchmarks for measuring reasoning v11. 0 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 v11. 8 claims were extracted from source literature; 2 were independently verified against retrieved documents. An…
Abstract: This report synthesises findings from 15 peer-reviewed papers addressing the following research question: How do multimodal language models perform on visual mathematical and scientific reasoning v11. 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: How does retrieval augmentation improve language model performance on knowledge-intensive tasks v11. 15 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: What training strategies improve language model generalization to novel mathematical reasoning problems v11. 12 claims were extracted from source literature; 1 was independently verified against retrieved…
Abstract: This report synthesises findings from 13 peer-reviewed papers addressing the following research question: What are the failure modes of frontier language models on abstract mathematical reasoning v11. 0 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 different finetuning strategies (e.g., parameter-efficient tuning vs. full finetuning) affect the scaling laws of LLMs on downstream tasks like MMLU or HellaSwag, measured by accuracy and. 0 claims were…
Abstract: This report synthesises findings from 12 peer-reviewed papers addressing the following research question: What is the effect of instruction fine-tuning on language model mathematical problem-solving accuracy v11. 19 claims were extracted from source literature; 1 was independently verified against retrieved…
Abstract: This report synthesises findings from 13 peer-reviewed papers addressing the following research question: What is the relationship between the amount of pretraining data and downstream task performance on multilingual benchmarks such as XTREME-R, when controlling for model size. 12 claims were extracted from source…
Abstract: This report synthesises findings from 13 peer-reviewed papers addressing the following research question: How does pretraining data quality affect language model reasoning benchmark performance v11. 11 claims were extracted from source literature; 0 were independently verified against retrieved documents. An…
Abstract: This report synthesises findings from 9 peer-reviewed papers addressing the following research question: What techniques enable language models to solve competition-level software engineering problems v11. 8 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 do language models perform on formal theorem proving and mathematical verification tasks v11. 14 claims were extracted from source literature; 1 was 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 v11. 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: What architectural innovations improve transformer performance on multi-step logical reasoning v11. 15 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: What is the relationship between model scale and emergent reasoning capabilities in transformers v11. 12 claims were extracted from source literature; 1 was independently verified against retrieved documents. An…
Abstract: This report synthesises findings from 16 peer-reviewed papers addressing the following research question: How does test-time compute scaling improve language model performance on reasoning benchmarks v11. 19 claims were extracted from source literature; 7 were independently verified against retrieved documents. An…