RePrompT: Recurrent Prompt Tuning for Integrating Structured EHR Encoders with Large Language Models

RePrompT: Recurrent Prompt Tuning for Integrating Structured EHR Encoders with Large Language Models | Signal Canvas | ScienceToStartup

Page Freshness

Signal Canvas proof surface

Canonical route: /signal-canvas/reprompt-recurrent-prompt-tuning-for-integrating-structured-ehr-encoders-with-large-language-models

stale

Proof freshness: stale
Proof status: unverified
Display score: 8/10
Last proof check: 2026-04-21
Score updated: 2026-04-21
Score fresh until: 2026-05-21
References: 0
Source count: 3
Coverage: 50%

This page is showing the last landed evidence receipt and score bundle because the latest proof data is outside the freshness window.

Agent Handoff

Canonical ID reprompt-recurrent-prompt-tuning-for-integrating-structured-ehr-encoders-with-large-language-models | Route /signal-canvas/reprompt-recurrent-prompt-tuning-for-integrating-structured-ehr-encoders-with-large-language-models

REST example

curl https://sciencetostartup.com/api/v1/agent-handoff/signal-canvas/reprompt-recurrent-prompt-tuning-for-integrating-structured-ehr-encoders-with-large-language-models

MCP example

{
  "tool": "search_signal_canvas",
  "arguments": {
    "mode": "paper",
    "paper_ref": "reprompt-recurrent-prompt-tuning-for-integrating-structured-ehr-encoders-with-large-language-models",
    "query_text": "Summarize RePrompT: Recurrent Prompt Tuning for Integrating Structured EHR Encoders with Large Language Models"
  }
}

source_context

{
  "surface": "signal_canvas",
  "mode": "paper",
  "query": "RePrompT: Recurrent Prompt Tuning for Integrating Structured EHR Encoders with Large Language Models",
  "normalized_query": "2604.17725",
  "route": "/signal-canvas/reprompt-recurrent-prompt-tuning-for-integrating-structured-ehr-encoders-with-large-language-models",
  "paper_ref": "reprompt-recurrent-prompt-tuning-for-integrating-structured-ehr-encoders-with-large-language-models",
  "topic_slug": null,
  "benchmark_ref": null,
  "dataset_ref": null
}

Evidence Receipt

Route status: building

Claims: 1

References: Pending verification

Proof: Verification pending

Freshness state: computing

Source paper: RePrompT: Recurrent Prompt Tuning for Integrating Structured EHR Encoders with Large Language Models

PDF: https://arxiv.org/pdf/2604.17725v1

Source count: 3

Coverage: 50%

Last proof check: 2026-04-21T02:39:24.229Z

Signal Canvas receipt window

Watch and verify: RePrompT: Recurrent Prompt Tuning for Integrating Structured EHR Encoders with Large Language Models

/buildability/reprompt-recurrent-prompt-tuning-for-integrating-structured-ehr-encoders-with-large-language-models

Watchwatch

Subject: RePrompT: Recurrent Prompt Tuning for Integrating Structured EHR Encoders with Large Language Models

Verdict

Watch

Verdict is Watch because viability or proof quality is intermediate and should be re-evaluated before execution.

RePrompT: Recurrent Prompt Tuning for Integrating Structured EHR Encoders with Large Language Models

Use Signal Canvas as the narrative proof surface

Use this Signal Canvas via API or MCP

Signal Canvas proof surface