Papers
Abstract: This report synthesises findings from 16 peer-reviewed papers addressing the following research question: What prompting strategies maximize language model accuracy on graduate-level science questions v10. 13 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 extended thinking time affect language model accuracy on competition-level mathematics v10. 12 claims were extracted from source literature; 2 were independently verified against retrieved documents. An…
Abstract: This report synthesises findings from 14 peer-reviewed papers addressing the following research question: How does synthetic training data improve language model performance on mathematical reasoning benchmarks v10. 0 claims were extracted from source literature; 0 were independently verified against retrieved…
Abstract: This report synthesises findings from 16 peer-reviewed papers addressing the following research question: How does model quantization affect reasoning capability in large language models v10. 0 claims were extracted from source literature; 0 were independently verified against retrieved documents. An automated…
Abstract: This report synthesises findings from 11 peer-reviewed papers addressing the following research question: How do language models handle multi-hop reasoning chains in scientific question answering v10. 11 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 is the effect of instruction fine-tuning on language model mathematical problem-solving accuracy v10. 9 claims were extracted from source literature; 4 were independently verified against retrieved…
Abstract: This report synthesises findings from 15 peer-reviewed papers addressing the following research question: What training strategies improve language model generalization to novel mathematical reasoning problems v10. 5 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 is the comparative performance of open-source language models versus proprietary models on coding benchmarks v10. 10 claims were extracted from source literature; 2 were independently verified against…
Abstract: This report synthesises findings from 4 peer-reviewed papers addressing the following research question: What are the failure modes of frontier language models on abstract mathematical reasoning v10. 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 does retrieval augmentation improve language model performance on knowledge-intensive tasks v10. 8 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 do multimodal language models perform on visual mathematical and scientific reasoning v10. 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 does reinforcement learning from human feedback improve language model mathematical reasoning v10. 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 do language models perform on formal theorem proving and mathematical verification tasks v10. 0 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 pretraining data quality affect language model reasoning benchmark performance v10. 12 claims were extracted from source literature; 1 was independently verified against retrieved documents. An automated…
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 v10. 8 claims were extracted from source literature; 6 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 v10. 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 is the relationship between model scale and emergent reasoning capabilities in transformers v10. 8 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 test-time compute scaling improve language model performance on reasoning benchmarks v10. 19 claims were extracted from source literature; 5 were independently verified against retrieved documents. An…
Abstract: This report synthesises findings from 14 peer-reviewed papers addressing the following research question: What are the scaling laws for chain-of-thought reasoning in large language models v10. 20 claims were extracted from source literature; 0 were independently verified against retrieved documents. An automated…
Abstract: This report synthesises findings from 12 peer-reviewed papers addressing the following research question: How do sparse mixture-of-experts models compare to dense transformers on mathematical reasoning v10. 11 claims were extracted from source literature; 0 were independently verified against retrieved documents. An…
Abstract: This report synthesises findings from 19 peer-reviewed papers addressing the following research question: Does the ENTROPY hypothesis (initial image size reduction) generalize to multimodal models (e.g., visual-language models like CLIP) when evaluating performance on cross-domain benchmarks (e.g., VCR. 18 claims…
Abstract: This report synthesises findings from 10 peer-reviewed papers addressing the following research question: How does the strategic exploration mechanism introduced in this paper scale with model size and affect the trade-off between alignment quality and inference efficiency, evaluated using the BIG-bench. 10 claims…
Abstract: This report synthesises findings from 14 peer-reviewed papers addressing the following research question: What is the impact of the KL-divergence constraint in the reverse-KL regularized contextual bandit formulation on the reasoning performance of aligned LLMs, as measured by the MMLU benchmark in. 0 claims were…
Abstract: This report synthesises findings from 12 peer-reviewed papers addressing the following research question: How does the iterative preference learning approach proposed in this paper compare to standard RLHF and DPO methods in terms of robustness on the AdversarialQA benchmark, when evaluated using metrics. 8 claims…
Abstract: This report synthesises findings from 15 peer-reviewed papers addressing the following research question: How does the proposed scaling law with learning rate annealing affect the alignment of code generation models across different programming languages in the LiveCodeBench dataset, as measured by. 15 claims were…