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SQaLe: A large text-to-SQL corpus grounded in real schemas
Get PDFAdvances in large language models have accelerated progress in text-to-SQL, methods for converting natural language queries into valid SQL queries. A key bottleneck for developing generalizable text-to-SQL models is the lack of large-scale datasets with sufficient schema and query complexity, domain coverage, and task diversity. We introduce SQaLe, a large-scale semi-synthetic text-to-SQL dataset built on 135,875 relational database schemas expanded from a collection of real-world schemas, SchemaPile. We establish a principled generation pipeline which combines schema sampling, question synthesis, and SQL construction, and produce 517,676 high-quality (question, schema, query) triples. The SQaLe dataset captures realistic schema size variability, diverse query patterns, and natural language ambiguity while maintaining execution validity. We provide an analysis of its contents and characteristics, and find that SQaLe introduces the most realistic large-scale text-to-SQL dataset to date in comparison with existing benchmarks and datasets. We discuss how SQaLe enables our vision for data scaling and model generalization in text-to-SQL research. The dataset is accessible at: https://huggingface.co/datasets/trl-lab/SQaLe-text-to-SQL-dataset
RCQoEA-360VR-Dataset: Real-time, continuous QoE scores for HMD-based 360° VR
No full textThe RCQoEA-360VR dataset is a novel multi-modal dataset designed for continuous QoE evaluation in virtual reality (VR) environments. The dataset contains continuous QoE annotations, synchronised physiological signals (ECG and GSR), behavioural data (eye and head movements) and post-viewing QoE ratings gathered through a within-VR interface from 32 participants. RCQoEA-360VR addresses a critical gap in existing public datasets by providing a fine-grained, synchronised multimodal data for immersive QoE analysis, as well as behavioural modelling, adaptive streaming, and implicit perceptual analysis
Haptic biosignals affect proxemics toward virtual reality agents
No full textEncounters with virtual agents currently lack the haptic viscerality of human contact. While digital biosignal communication can mediate such virtual social interactions, how artificial haptic biosignals influence users’ personal space during Virtual Reality (VR) experiences is unknown. Designing vibrotactile heartbeats and thermally-actuated body temperature, we ran a within-subjects study (N=31) to investigate feedback (Thermal, Vibration, Thermal+Vibration, None) and agent stories (Negative, Neutral, Positive) on objective and subjective interpersonal distance (IPD), perceived arousal and comfort, presence, and post-experience responses. Findings showed that thermal feedback decreased objective but not subjective IPD, whereas vibrotactile heartbeats (signaling agent's closeness) increased both while heightening arousal and discomfort. Agents' stories did not affect IPD, arousal, or comfort. Our qualitative findings shed light on signal ambiguity and presence constructs within VR-based haptic stimulation. We contribute insights into artificial biosignals and their influence on VR proxemics, with cautionary considerations should the boundaries blur between physical and virtual touch
Predicting the outcome of ongoing automated negotiations
Get PDFEstimating the outcome of a negotiation before it is finished allows a party to take effective actions, e.g., exploring outside options, or reporting progress to a human user. However, estimating the outcome is difficult as many (uncertain) factors affect the course of a negotiation. Accordingly, this paper presents a method for predicting the outcome of ongoing bilateral negotiations called PrONeg. We predict the future trajectories of an agent’s own bids and its opponent’s bids using time series forecasting methods. These forecasts are used to determine the agent’s outcome utility distribution, along with the probability of reaching an agreement by the end of the negotiation. Finally, we predict the most likely outcome of the negotiation by combining the outcome utility distribution with preference information available in the negotiation scenario. Our experiments show that Gaussian processes perform best in most settings, including balancing predicting true breakoffs without misclassifying agreements. With its ability to predict the outcome of a negotiation, PrONeg can potentially serve as a negotiation support system in hybrid negotiations
Uncovering manipulation techniques in Virtual Reality
No full textOpen your favourite travel or clothing app and soon you will discover so-called ‘dark design patterns’, subtle techniques that encourage you to spend money. These patterns are mostly visual, but with the rise of VR, sound and touch-based techniques can also be used. Researchers Gijs Huisman and Karthik Venkatraj have designed a VR demo highlighting some of these touch-based techniques. “We want people to be aware of manipulative potential that new technologies like VR pose.
Samenwerken in virtual reality: wat Lego ons leert over menselijke connectie
No full textWat gebeurt er als je samen een Legofiguur moet bouwen, maar je collega hoort en ziet alles met vertraging? In een experiment in virtual reality toont menselijke connectie zich verrassend veerkrachtig: zelfs binnen technologische beperkingen blijven mensen efficiënt samenwerken
CacheGuardian: A timing side-channel resilient LLC design
Get PDFIn cloud computing environments, the last-level cache (LLC) shared by multiple tenants is frequently exploited through timing side-channel attacks, enabling unauthorized data leakage. To address this issue, various defense mechanisms have been proposed. However, existing works exhibit deficiencies in terms of performance overhead, coverage of attacks, and detection accuracy. In response to these challenges, we propose CacheGuardian, a hardware-based LLC protection design which aims to provide stronger, broader, and more accurate protection against timing side-channel attacks with low performance overhead. It includes: (1) A behavior-based, generic attack detector capable of identifying multiple timing side-channel attacks in real time; (2) A cache-set-level access control mechanism that strictly restricts cache usage exclusively for the identified attackers instead of influencing all security domains.We implement our design in a gem5 simulator to evaluate both its security and performance. Our proof-of-concept attacks and SPEC 2017 benchmarks show that our design is effective against a wide range of timing side-channel attacks, reducing attack success rates by up to 256×, including camouflaged variants. Moreover, it improves the performance of benign workloads by an average of 2.26% with only 2.4% storage overhead