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165
datasets available to search
ShareScore release 0.9.0
Dataset results
165 results for “prompting”
SAGA is important for prompt export of stress-inducible transcripts through Sgf73p-mediated mechanism
GEO Series GSE116228. Saccharomyces cerevisiae. 21 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
An aberrant resurrection of endogenous retrovirus prompts acute myocarditis and heart failure
GEO Series GSE274895. Mus musculus. 19 samples. Type: Expression profiling by high throughput sequencing; Genome binding/occupancy profiling by high throughput sequencing; Methylation profiling by high throughput sequencing.
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>
【outputs_encode_to_representations】only two 8B LLMs, only FB task, only augmented responses language materials w/o their representations, no original prompt or response
<ul> <li>only two 8B LLMs,</li> <li>only FB task,</li> <li>only augmented responses language materials w/o their representations, no original prompt or response</li> <li>19 (valid prompts) ⨉ 2 (LLMs) = 38 (files)</li> </ul>
【outputs_encode_to_representations】only two 8B LLMs, only Hinting task, only augmented responses language materials w/o their representations, no original prompt or response
<ul> <li>only two 8B LLMs, only Hinting task,</li> <li>only augmented responses language materials w/o their representations,</li> <li>no original prompt or response,</li> <li>13 (valid prompts) ⨉ 2 (scores) = 26 files</li> </ul>
【outputs_encode_to_representations】only two 8B LLMs, only Ir task, only augmented responses language materials w/o their representations, no original prompt or response
<ul> <li>only two 8B LLMs,</li> <li>only Ir task, only augmented responses language materials w/o their representations,</li> <li>no original prompt or response,</li> <li>12 (valid prompts) ⨉ 2 (scores) = 24 files</li> </ul>
【outputs_encode_to_representations】only two 8B LLMs, only SS task, augmented responses representations w/o their language materials, w/ original prompt and response representations
<ul> <li>only two 8B LLMs,</li> <li>only SS task,</li> <li>augmented responses representations w/o their language materials,<br> <ul> <li>12 (valid prompts), 2 (LLMs), 2 (Scores)</li> <li>16 ⨉ 2 (LLMs) = 32 files</li> </ul> </li> <li>original prompt and response representations <ul> <li>[1 (prompt) + 1 (response)] ⨉ 2 (LLMs) = 4 files</li> </ul> </li> <li>in total, 32 + 4 = 36 files</li> </ul>
【outputs_encode_to_representations】only two 8B LLMs, only Ir task, augmented responses representations w/o their language materials, w/ original prompt and response representations
<ul> <li>only two 8B LLMs,</li> <li>only Ir task, augmented responses representations w/o their language materials,<br> <ul> <li>12 (valid prompts) ⨉ 2 (LLMs) ⨉ 2 (scores) = 48 files</li> </ul> </li> <li>original prompt and response representations <ul> <li>[1 (prompt) + 1 (response)] ⨉ 2 (LLMs) = 4 files</li> </ul> </li> <li>in total, 48 + 4 = 52 files</li> </ul>
【outputs_encode_to_representations】only two 8B LLMs, only Hinting task, augmented responses representations w/o their language materials, w/ original prompt and response representations
<ul> <li>only two 8B LLMs, only Hinting task,</li> <li>augmented responses representations w/o their language materials,<br> <ul> <li>13 (valid prompts) ⨉ 2 (LLMs) ⨉ 2 (scores) = 52 files</li> </ul> </li> <li>original prompt and response representations, <ul> <li>[1 (prompt) + 1 (response)] ⨉ 2 (LLMs) = 4 files</li> </ul> </li> <li>in total, 52 + 4 = 56 files</li> </ul>
【outputs_encode_to_representations】only two 8B LLMs, only SS 012 task, only augmented responses language materials w/o their representations, no original prompt or response
<ul> <li>only two 8B LLMs,</li> <li>only SS 012 task, only augmented responses language materials w/o their representations,</li> <li>no original prompt or response language materials</li> <li>7 (valid prompts) ⨉ 1 (Score) = 7 files</li> </ul>
【outputs_encode_to_representations】only two 8B LLMs, only SS task, only augmented responses language materials w/o their representations, no original prompt or response
<ul> <li>only two 8B LLMs,</li> <li>only SS task,</li> <li>only augmented responses language materials w/o their representations,</li> <li>no original prompt or response language materials</li> <li>12 (valid prompts), 2 (Scores)</li> <li>16 files</li> </ul>
【outputs_encode_to_representations】only two 8B LLMs, only FB task, augmented responses representations w/o their language materials, w/ original prompt and response representations
<ul> <li>only two 8B LLMs</li> <li>only FB task</li> <li>augmented responses representations w/o their language materials <ul> <li>19 (valid prompts) ⨉ 2 (LLMs) ⨉ 2 (scores) = 76 files </li> </ul> </li> <li>original prompt and response representations <ul> <li>[1 (prompt) + 1 (response)] ⨉ 2 (LLMs) = 4 files</li> </ul> </li> <li>in total, 76 + 4 = 80 files</li> </ul>
【outputs_encode_to_representations】only two 8B LLMs, only SS 012 task, augmented responses representations w/o their language materials, w/ original prompt and response representations
<ul> <li>only two 8B LLMs,</li> <li>only SS 012 task, only augmented responses representations w/o their language materials,<br> <ul> <li>7 (valid prompts) ⨉ 2 (LLMs) ⨉ 1 (Scores) = 14 files</li> </ul> </li> <li>original prompt and response representations <ul> <li>1 (response) ⨉ 2 (LLMs) = 2 files</li> </ul> </li> <li>in total, 14 + 2 = 16 files</li> </ul>
【outputs_encode_to_representations】only two 70B LLMs, only Hinting task, only augmented responses language materials w/o their representations, no original prompt or response
<ul> <li>only two 70B LLMs,</li> <li>only Hinting task,</li> <li>only augmented responses language materials w/o their representations,</li> <li>no original prompt or response,</li> <li>13 (valid prompts) ⨉ 2 (scores) = 26 files</li> </ul>
【outputs_encode_to_representations】only two 70B LLMs, only FB task, only augmented responses language materials w/o their representations, no original prompt or response
<ul> <li>only two 70B LLMs, </li> <li>only FB task,</li> <li>only augmented responses language materials w/o their representations,</li> <li>no original prompt or response,</li> <li>19 (valid prompts) ⨉ 2 (scores) = 38 files</li> </ul>
【outputs_encode_to_representations】only two 70B LLMs, only Ir task, only augmented responses language materials w/o their representations, no original prompt or response
<ul> <li>only two 70B LLMs,</li> <li>only Ir task,</li> <li>only augmented responses language materials w/o their representations,</li> <li>no original prompt or response,</li> <li>12 (valid prompts) ⨉ 2 (scores) = 24 files</li> </ul>
【outputs_encode_to_representations】only two 70B LLMs, only SS 012 task, only augmented responses language materials w/o their representations, no original prompt or response
<ul> <li>only two 70B LLMs,</li> <li>only SS 012 task,</li> <li>only augmented responses language materials w/o their representations,</li> <li>no original prompt or response language materials</li> <li>7 (valid prompts) ⨉ 1 (Score) = 7 files</li> </ul>
【outputs_encode_to_representations】only two 70B LLMs, only SS task, only augmented responses language materials w/o their representations, no original prompt or response
<ul> <li>only two 70B LLMs,</li> <li>only SS task,</li> <li>only augmented responses language materials w/o their representations,</li> <li>no original prompt or response language materials</li> <li>12 (valid prompts), 2 (Scores), 16 files</li> </ul>
【outputs_encode_to_representations】only two 70B LLMs, only Hinting task, augmented responses representations w/o their language materials, w/ original prompt and response representations
<ul> <li>only two 70B LLMs,</li> <li>only Hinting task, augmented responses representations w/o their language materials, <ul> <li>13 (valid prompts) ⨉ 2 (LLMs) ⨉ 2 (scores) = 52 files</li> </ul> </li> <li>original prompt and response representations, <ul> <li>[1 (prompt) + 1 (response)] ⨉ 2 (LLMs) = 4 files</li> </ul> </li> <li>in total, 52 + 4 = 56 files</li> </ul>
【outputs_encode_to_representations】only two 70B LLMs, only FB task, augmented responses representations w/o their language materials, w/ original prompt and response representations
<ul> <li>only two 70B LLMs</li> <li>only FB task augmented responses representations w/o their language materials <ul> <li>19 (valid prompts) ⨉ 2 (LLMs) ⨉ 2 (scores) = 76 files </li> </ul> </li> <li>original prompt and response representations <ul> <li>[1 (prompt) + 1 (response)] ⨉ 2 (LLMs) = 4 files</li> </ul> </li> <li>in total, 76 + 4 = 80 files</li> </ul>
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.