Paper Citation Record · LEDGER

Hard Prompts Made Easy: Gradient-Based Discrete Optimization for Prompt Tuning and Discovery

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 12 inbound Pith citation observations for arXiv:2302.03668.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2302.03668 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 12 of 12 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 12 of 12 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T20:08:13.579248Z

measured 1 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

40
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation e62e4a33-f511-4137-b300-e7a0247455d2 · inbound

Universal and Transferable Adversarial Attacks on Aligned Language Models cites this paper.

Universal and Transferable Adversarial Attacks on Aligned Language Models Hard Prompts Made Easy: Gradient-Based Discrete Optimization for Prompt Tuning and Discovery

Reference 26

Resolution: verified exact; arxiv_id, observed 2026-05-24T07:44:08.477006Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 300773cb-bd2b-4e22-bccf-48840696baaf · inbound

Baseline Defenses for Adversarial Attacks Against Aligned Language Models cites this paper.

Baseline Defenses for Adversarial Attacks Against Aligned Language Models Hard Prompts Made Easy: Gradient-Based Discrete Optimization for Prompt Tuning and Discovery

Reference 60

Resolution: verified exact; arxiv_id, observed 2026-05-13T23:24:40.233850Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 51790050-753c-41c9-85e3-dbe3c1a4ef79 · inbound

Large Language Models as Optimizers cites this paper.

Large Language Models as Optimizers Hard Prompts Made Easy: Gradient-Based Discrete Optimization for Prompt Tuning and Discovery

Reference 41

Resolution: verified exact; arxiv_id, observed 2026-05-15T00:04:31.331797Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 6cabf74e-7312-417c-bcf0-39cae94646a8 · inbound

Catastrophic Jailbreak of Open-source LLMs via Exploiting Generation cites this paper.

Catastrophic Jailbreak of Open-source LLMs via Exploiting Generation Hard Prompts Made Easy: Gradient-Based Discrete Optimization for Prompt Tuning and Discovery

Reference 22

Resolution: verified exact; arxiv_id, observed 2026-05-16T22:00:51.523673Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 3b83d5ef-48a3-4636-bcd8-0ba06aae57cc · inbound

CodeSCM: Causal Analysis for Multi-Modal Code Generation cites this paper.

CodeSCM: Causal Analysis for Multi-Modal Code Generation Hard Prompts Made Easy: Gradient-Based Discrete Optimization for Prompt Tuning and Discovery

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-08T20:08:13.579248Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c899c6ad-5ee1-4016-b8f2-01d072ed3f1f · inbound

Efficient and Privacy-Preserving Soft Prompt Transfer for LLMs cites this paper.

Efficient and Privacy-Preserving Soft Prompt Transfer for LLMs Hard Prompts Made Easy: Gradient-Based Discrete Optimization for Prompt Tuning and Discovery

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-06T23:51:21.598507Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b7a7328c-8340-48e1-80ab-455201ea28bc · inbound

Does Your VFM Speak Plant? The Botanical Grammar of Vision Foundation Models for Object Detection cites this paper.

Does Your VFM Speak Plant? The Botanical Grammar of Vision Foundation Models for Object Detection Hard Prompts Made Easy: Gradient-Based Discrete Optimization for Prompt Tuning and Discovery

Reference 22

Resolution: verified exact; arxiv_id, observed 2026-05-11T07:35:57.239935Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation bfe18aeb-7c28-4f79-b4e2-2a1ec683451c · inbound

Adaptive Prompt Embedding Optimization for LLM Jailbreaking cites this paper.

Adaptive Prompt Embedding Optimization for LLM Jailbreaking Hard Prompts Made Easy: Gradient-Based Discrete Optimization for Prompt Tuning and Discovery

Reference 27

Resolution: verified exact; arxiv_id, observed 2026-05-11T22:06:14.415802Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation b9724111-e5c8-4c01-8264-379b0c32b24d · inbound

Guaranteed Jailbreaking Defense via Disrupt-and-Rectify Smoothing cites this paper.

Guaranteed Jailbreaking Defense via Disrupt-and-Rectify Smoothing Hard Prompts Made Easy: Gradient-Based Discrete Optimization for Prompt Tuning and Discovery

Reference 36

Resolution: metadata mismatch; arxiv_id, observed 2026-05-12T05:51:27.506593Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation b2668995-6299-4751-8aee-ae380075cc72 · inbound

Learning, Fast and Slow: Towards LLMs That Adapt Continually cites this paper.

Learning, Fast and Slow: Towards LLMs That Adapt Continually Hard Prompts Made Easy: Gradient-Based Discrete Optimization for Prompt Tuning and Discovery

Reference 62

Resolution: verified exact; arxiv_id, observed 2026-05-13T05:07:18.473989Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation a647a829-99fd-4c81-ad82-686a3a286361 · inbound

Learning, Fast and Slow: Towards LLMs That Adapt Continually cites this paper.

Learning, Fast and Slow: Towards LLMs That Adapt Continually Hard Prompts Made Easy: Gradient-Based Discrete Optimization for Prompt Tuning and Discovery

Reference 63

Resolution: verified exact; arxiv_id, observed 2026-05-15T05:19:45.658422Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation a10deb94-6725-4814-b361-f2bebb4ad4a1 · inbound

PRISM: Recovering Instruction Sets from Language Model Activations cites this paper.

PRISM: Recovering Instruction Sets from Language Model Activations Hard Prompts Made Easy: Gradient-Based Discrete Optimization for Prompt Tuning and Discovery

Reference 51

Resolution: verified exact; arxiv_id, observed 2026-06-27T17:01:08.060750Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.