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LLMs can learn self-restraint through iterative self-reflection
In order to be deployed safely, Large Language Models (LLMs) must be capable of dynamically adapting their behavior based on their …
LitLLMs, LLMs for Literature Review: Are We There Yet?

Literature reviews are an essential component of scientific research, but they remain time-intensive and challenging to write, …

Deep Learning in Ultrasound localization Microscopy: Applications and perspectives
Ultrasound Localization Microscopy (ULM) is a novel super-resolution imaging technique that can image the vasculature in vivo at depth …
Pruning Sparse Tensor Neural Networks Enables Deep Learning for 3D Ultrasound Localization Microscopy
Ultrasound Localization Microscopy (ULM) is a non-invasive technique that allows for the imaging of micro-vessels in vivo, at depth and …
Bidding in day-ahead electricity markets: A dynamic programming framework
Strategic bidding problems have gained a lot of attention with the introduction of deregulated electricity markets where producers and …
The BrowserGym Ecosystem for Web Agent Research
The BrowserGym ecosystem addresses the growing need for efficient evaluation and benchmarking of web agents, particularly those …
Exploring validation metrics for offline model-based optimisation with diffusion models
In model-based optimisation (MBO) we are interested in using machine learning to design candidates that maximise some measure of reward …
Evaluating Correctness and Faithfulness of Instruction-Following Models for Question Answering
Retriever-augmented instruction-following models are attractive alternatives to fine-tuned approaches for information-seeking tasks …
On Stochastic Mirror Descent: Convergence Analysis and Adaptive Variants
We investigate the convergence of stochastic mirror descent (SMD) under interpolation in relatively smooth and smooth convex …