Collaborative AI Agents in the Era of Large Language Models

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Early work has found that large language models (LLMs) can generate persuasive content. However, evidence on whether they can also personalize arguments to individual attributes remains limited, despite being crucial for assessing misuse. This preregistere ...

Photorealistic synthetic data and novel rendering techniques significantly advanced computer vision research. However, datasets focused on computer vision applications cannot be easily applied to robotics because they typically lack physics-related informa ...

Given a ground-level query image and a geo-referenced aerial image that covers the query’s local surroundings, fine-grained cross-view localization aims to estimate the location of the ground camera inside the aerial image. Recent works have focused on dev ...

Bridging the performance gap between robotics and biological systems demands significant advancements across multiple domains, including mechanical design, control theory, modeling, and artificial intelligence. In this thesis, I will introduce innovative m ...

Self-supervised pretrained models exhibit competitive performance in automatic speech recognition (ASR) on finetuning, even with limited in-domain supervised data. However, popular pretrained models are not suitable for streaming ASR because they are train ...

MammAlps is a multimodal and multi-view dataset of wildlife behavior monitoring. Nine camera-traps were placed at three monitoring sites in the Swiss National Park, from which we curated over 14 hours of video with audio, 2D segmentation maps and 8.5 hours ...

Faithful human performance capture and free-view rendering from sparse RGB observations is a long-standing problem in Vision and Graphics. The main challenges are the lack of observations and the inherent ambiguities of the setting, e.g. occlusions and dep ...

Machine learning is increasingly integrated with decision making by powering automated systems and informing human decision makers in applications such as CV screening, portfolio allocation, loan risk assessment, and insurance approval. In this thesis, I e ...

Context: The use of evidence in policymaking can take various forms, and resorting to quantitative indicators is one of them. In the past 30 years, a plethora of indicator-based initiatives for assessing and monitoring progress towards sustainability have ...

Driving continuous, low-power artificial intelligence (AI) in the Internet of Things (IoT) requires reliable energy harvesting and storage under indoor or low-light conditions, where batteries face constraints such as finite lifetimes and increased environ ...

The optimistic gradient method is useful in addressing minimax optimization problems. Motivated by the observation that the conventional stochastic version suffers from the need for a large batch size on the order of O(ϵ-2) to achieve an ϵ-stationary solut ...

Object detection, a fundamental task in computer vision, is crucial for various intelligent edge computing applications. However, object detection algorithms are usually heavy in computation, hindering their deployments on resource-constrained edge devices ...

In the rapidly evolving AI era with large language models (LLMs) at the core, making LLMs more trustworthy and efficient, especially in output generation (inference), has gained significant attention. This is to reduce plausible but faulty LLM outputs (a.k ...

Articulating the interplay between collective memory and artificial intelligence, this paper examines the SAILDART archive, a unique digital collection derived from the backup tapes of the Stanford Artificial Intelligence Laboratory (SAIL). Preserved somew ...

Collaborative AI Agents in the Era of Large Language Models

Chat with Graph Search

On the conversational persuasiveness of GPT-4

GRADE: Generating Realistic and Dynamic Environments for robotics research with Isaac Sim

Adapting Fine-Grained Cross-View Localization to Areas Without Fine Ground Truth

Design of robotic physical intelligence

XLSR-Transducer: Streaming ASR for Self-Supervised Pretrained Models

MammAlps: A multi-view video behavior monitoring dataset of wild mammals in the Swiss Alps

MetaCap: Meta-learning Priors from Multi-view Imagery for Sparse-View Human Performance Capture and Rendering

Machine Learning in Decision-Making Systems: Fairness, Robustness, and Data Bias

Application and use of sustainability indicators by local governments, and their determinants: a Swiss case study

Unlocking high-performance photocapacitors for edge computing in low-light environments

Diffusion Stochastic Optimization for Min-Max Problems

Edge-Cloud Collaborated Object Detection via Bandwidth Adaptive Difficult-Case Discriminator

Trustworthy and Efficient LLMs Meet Databases

Collective Memory Through Computer Memories: Retracing and Interpreting the Archive of the Stanford Artificial Intelligence Laboratory