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Dataset results
165 results for “prompting”
High time resolution search for prompt radio emission from the long GRB 210419A with the Murchison Widefield Array
<p>The time series of Stokes parameters in the PSRFITS format formed from the MWA data at the position of GRB 210419A.</p>
VIMA: General Robot Manipulation with Multimodal Prompts
<p>VIMA dataset for learning general robot manipulation with multimodal prompts.</p>
Dataset for Automated Unit Test Generation via Chain of Thought Prompt and Reinforcement Learning
<p>This is the replication package including three types datasets: training dataset with CoT prompts, reward dataset for training reward model, rl dataset for optimizing policy model. The training dataset includes filter_test_cot_rule_50k.csv, filter_train_cot_rule_50k.csv, and filter_valid_cot_rule_50k.csv. These three datasets includes multiple fields (i.e., src_fm, intention, plan, elaboration, gpt_test, src_fm_cot_gpt, target, src_fm_fc_ms_ff,src_fm_intention,src_fm_plan,src_fm_elaboration,idx,rule_cot,rule_cot_nlp,combine_cot,src_fm_rule_cot_nlp,src_fm_cot_nlp_gpt,gpt_cot_filter,src_fm_plan_intention). The reward dataset includes test_athena.json, train_athena.json, and valid_athena.json three files. The rl dataset includes three files: filter_test_cot_gpt_rl.csv, filter_train_cot_gpt_rl.csv, filter_valid_cot_gpt_rl.csv. These files include mulitple fields: src_fm,intention,plan,elaboration,gpt_test,src_fm_cot_gpt,target,src_fm_fc_ms_ff,src_fm_intention,src_fm_plan,src_fm_elaboration,gpt_cot_filter.</p>
SAC Prompting at Specific Intensities
Open the record for dataset details and reuse information.
Functional and morphological adaptation in DNA protocells via signal processing prompted by artificial metalloenzymes
<p>Data underlying the figures in the publication “Functional and morphological adaptation in DNA protocells via signal processing prompted by artificial metalloenzymes”, published in<em> Nat. Nanotechnol., </em><strong>2020</strong>, 15, 914–921. <a href="https://doi.org/10.1038/s41565-020-0761-y">https://doi.org/10.1038/s41565-020-0761-y</a></p> <p>Table of contents:</p> <p><strong>1. Dataset</strong>; Excel file containing the numerical data for <em>Figure 3</em>: Metathesis kinetics, mutant screenings and crowding.</p> <p><strong>2. Experimental Information</strong>; Word file containing the experimental protocols for synthesis and analysis.</p> <p> </p> <p> </p>
Data from: Consequences of aboveground invasion by non-native plants into restored vernal pools do not prompt changes in belowground processes
<p>Given the frequent overlap between biological plant invasion and ecological restoration efforts it is important to investigate their interactions to sustain desirable plant communities and modify long-term legacies both above and belowground. To address this relationship, we used natural reference, invaded, and constructed vernal pools in the Central Valley of California to examine potential changes in direct and indirect plant effects on soils associated with biological invasion and active restoration ecosystem disturbances. Our results showed that through a shift in vegetation composition and changes in the plant community tissue chemistry, invasion by non-native plant species has the potential to transform plant inputs to soils in vernal pool systems. In particular, we found that while non-native litter decomposition was driven by seasonal and interannual variability, associated with changes in precipitation, the overall decomposition for non-native litter was drastically lower than native species. This shift has important implications for long-term alterations in plant-based inputs to soils in a negative feedback to nutrient cycling. Moreover, these results were independent of historic active restoration efforts. Despite the consistent shift in plant litter decomposition rates and community composition, we did not detect associated shifts in belowground function associated with invasion by non-native plants. Instead, soil C:N ratios and microbial biomass did not differ between invaded and reference naturally occurring pools but were reduced in the manipulated restored pools independent of invasion levels. Our results suggest that while there is an observed invasive positive feedback aboveground, this trajectory is not necessarily represented belowground and restoration legacies were still dominant ten years after practices were applied. Restoration practices that limit invasive plant feedbacks and account for soil legacy recovery, therefore offer the best solution for disturbed ephemeral ecosystems.</p>
Piloting Copilot and Codex: Hot Temperature, Cold Prompts, or Black Magic? - Data
<p>Generated programs from <a href="https://arxiv.org/abs/2210.14699">Piloting Copilot and Codex: Hot Temperature, Cold Prompts, or Black Magic?</a></p>
NapSS: Paragraph-level Medical Text Simplification via Narrative Prompting and Sentence-matching Summarization
<p>Accessing medical literature is difficult for laypeople as the content is written for specialists and contains medical jargon. Automated text simplification methods offer a potential means to address this issue. In this work, we propose a summarize-then-simplify two-stage strategy, which we call NapSS, identifying the relevant content to simplify while ensuring that the original narrative flow is preserved. In this approach, we first generate reference summaries via sentence matching between the original and the simplified abstracts. These summaries are then used to train an extractive summarizer, learning the most relevant content to be simplified. Then, to ensure the narrative consistency of the simplified text, we synthesize auxiliary narrative prompts combining key phrases derived from the syntactical analyses of the original text. Our model achieves results significantly better than the seq2seq baseline on an English medical corpus, yielding 3%~4% absolute improvements in terms of lexical similarity, and providing a further 1.1% improvement of SARI score when combined with the baseline. We also highlight shortcomings of existing evaluation methods, and introduce new metrics that take into account both lexical and high-level semantic similarity. A human evaluation conducted on a random sample of the test set further establishes the effectiveness of the proposed approach.</p>
Prompting Creative Requirements via Traceable and Adversarial Examples in Deep Learning
<p>File A: Datasets (.txt)</p> <p> A1: Webex</p> <p> A2: Zoom</p> <p> A3: Teams</p> <p> A4: Word</p> <p> A5: PowerPoint</p> <p> A6: Excel</p> <p>File B: Python Code (Both ours and baseline)</p> <p> B1: pert_class.ipynb</p> <p> B2: Baseline.ipynb</p> <p>File C: Trend of Adversarial Shifts (Graphs)</p> <p> C1: Webex Adversarial Shifts</p> <p> C2: Zoom Adversarial Shifts</p> <p> C3: Teams Adversarial Shifts</p> <p> C4: Word Adversarial Shifts</p> <p> C5: Powerpoint Adversarial Shifts</p> <p> C6: Excel Adversarial Shifts</p> <p>File D: Trend of Non-Adversarial Shifts (Graphs)</p> <p> D1: Webex Non-Adversarial Shifts</p> <p> D2: Zoom Non-Adversarial Shifts</p> <p> D3: Teams Non-Adversarial Shifts</p> <p> D4: Word Non-Adversarial Shifts</p> <p> D5: Powerpoint Non-Adversarial Shifts</p> <p> D6: Excel Non-Adversarial Shifts</p> <p> </p> <p> </p>
Replication Package for "Are Prompt Engineering and TODO Comments Friends or Foes? An Evaluation on GitHub Copilot"
<p>This is the replication package accompanying the submission of "Are Prompt Engineering and TODO Comments Friends or Foes? An Evaluation on GitHub Copilot"</p>
Prepare for your next consultation with your health care provider - patient questions prompt list
<p>A list of questions patients with cancer and multimorbidity can use to be better prepared for their next consultation with their health care provider.</p>
Trial of Prompt Mental Health Care
ClinicalTrials.gov study NCT03238872. IPD Sharing: Not stated. Countries: 1. Publications: 4.
ECG Methods for the Prompt Identification of Coronary Events
ClinicalTrials.gov study NCT04237688. IPD Sharing: NO. Countries: 1. Publications: 4.
Sepsis Electronic Prompting for Timely Intervention and Care for Inpatients
ClinicalTrials.gov study NCT06117618. IPD Sharing: NO. Countries: 1. Publications: 1.
Point-of-Choice Prompts to Reduce Prolonged Sitting Time at Work
ClinicalTrials.gov study NCT01628861. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Sepsis Electronic Prompting for Timely Intervention and Care for Emergency Department Patients
ClinicalTrials.gov study NCT06117605. IPD Sharing: NO. Countries: 1. Publications: 1.
Effect of Prompting the Supply of Zinc/LO-ORS Co-packs in the Private Sector Plus BCI on Childhood Diarrhea Treatment
ClinicalTrials.gov study NCT04335877. IPD Sharing: NO. Countries: 1. Publications: 12.
Development of a Mobile Application for HBB Prompt Study
ClinicalTrials.gov study NCT03577054. IPD Sharing: UNDECIDED. Countries: 1. Publications: 10.
Diabetes Electronic Prompt for Improved Care Coordination and Treatment in the ED
ClinicalTrials.gov study NCT06899191. IPD Sharing: YES. Countries: 1. Publications: 14.
Feasibility and Utilization of an Application-based Question Prompt List
ClinicalTrials.gov study NCT03676920. IPD Sharing: Not stated. Countries: 1. Publications: 1.
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.