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Paper Citation Record · LEDGER

DT-Guard: Intent-Driven Reasoning-Active Training for Reasoning-Free LLM Safety Guardrail

As of 20 August 2026, this Paper Citation Record lists 20 of 20 outbound references and 0 inbound Pith citation observations for arXiv:2607.06326.

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

pith.paper-citation-record.v1
2607.06326 v1

Coverage vector

measured 20 of 20 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-08T10:00:02.677030Z

measured 20 of 20 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

20 of 20 outbound references displayed

  • verified exact9
  • verified fuzzy9
  • unresolved1
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f903cd5a-a784-4697-93c0-33113a0b54f2 · outbound

This paper cites Qwen3.5: Accelerating productivity with native multimodal agents, February.

DT-Guard: Intent-Driven Reasoning-Active Training for Reasoning-Free LLM Safety Guardrail Qwen3.5: Accelerating productivity with native multimodal agents, February

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-07-08T10:04:52.367516Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-07-08T10:00:02.677030Z digest=sha256:65a643b95804b1f0354200cebe6d56560e2c871dda3ae958efb080540a81d23c

Observation ece7e816-b4be-4f33-9812-a16bf39a369a · outbound

This paper cites an unresolved cited work.

DT-Guard: Intent-Driven Reasoning-Active Training for Reasoning-Free LLM Safety Guardrail Unresolved cited work

Reference 2

Resolution
unresolved
raw_fallback, observed 2026-07-08T10:04:52.371305Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-07-08T10:00:02.677030Z digest=sha256:7cd829e6a9e000dff2bf50c148eee02f2c9d778e348d6ed09686a5ff7e40c991

Observation cd6f2c40-2d6b-4741-a70e-0b1b8d67dab3 · outbound

This paper cites OpenAI GPT-5 System Card.

DT-Guard: Intent-Driven Reasoning-Active Training for Reasoning-Free LLM Safety Guardrail OpenAI GPT-5 System Card

Reference 3

Resolution
verified exact
local_arxiv, observed 2026-07-08T10:04:51.397330Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-07-08T10:00:02.677030Z digest=sha256:d68170c6695dec05f8cb6f08d59ced3fe1687ea16decf621ab06b5dd7dbe80cc

Observation 96ab69ce-f21f-4b83-9729-367897534010 · outbound

This paper cites Ling and Ring 2.6 Technical Report: Efficient and Instant Agentic Intelligence at Trillion-Parameter Scale.

DT-Guard: Intent-Driven Reasoning-Active Training for Reasoning-Free LLM Safety Guardrail Ling and Ring 2.6 Technical Report: Efficient and Instant Agentic Intelligence at Trillion-Parameter Scale

Reference 4

Resolution
verified exact
local_arxiv, observed 2026-07-08T10:04:51.450608Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-07-08T10:00:02.677030Z digest=sha256:1fe198f014e08a4f4f418a806e9f50807991b50ed7b13c0368c2b91f5ba6ebff

Observation 0746d725-cd52-405d-a106-c15c204f3774 · outbound

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

DT-Guard: Intent-Driven Reasoning-Active Training for Reasoning-Free LLM Safety Guardrail Universal and Transferable Adversarial Attacks on Aligned Language Models

Reference 5

Resolution
metadata mismatch
local_arxiv, observed 2026-07-08T10:04:51.422122Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-07-08T10:00:02.677030Z digest=sha256:68f983952793b00a7def2c6403e9d8e56927129f733606abe376f6a24d095fff

Observation 719abebe-bc9b-455c-8278-5b1989d47931 · outbound

This paper cites AutoDAN: Interpretable Gradient-Based Adversarial Attacks on Large Language Models.

DT-Guard: Intent-Driven Reasoning-Active Training for Reasoning-Free LLM Safety Guardrail AutoDAN: Interpretable Gradient-Based Adversarial Attacks on Large Language Models

Reference 6

Resolution
verified exact
local_arxiv, observed 2026-07-08T10:04:51.416555Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-07-08T10:00:02.677030Z digest=sha256:3c97a13ebfee0e41db43f5e0079a1a800d19219c70382d35182f02a6260c9833

Observation e3721611-9e13-434d-969d-772c93d684aa · outbound

This paper cites Llama Guard: LLM-based Input-Output Safeguard for Human-AI Conversations.

DT-Guard: Intent-Driven Reasoning-Active Training for Reasoning-Free LLM Safety Guardrail Llama Guard: LLM-based Input-Output Safeguard for Human-AI Conversations

Reference 7

Resolution
verified exact
local_arxiv, observed 2026-07-08T10:04:51.433560Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-07-08T10:00:02.677030Z digest=sha256:2d36d19960e381f0d5f872a17006ab0eb162b14995b8b297f4754d67f9997a78

Observation e21251d7-1518-48ce-aca3-70e656775904 · outbound

This paper cites Shieldgemma: Generative ai content moderation based on gemma,.

DT-Guard: Intent-Driven Reasoning-Active Training for Reasoning-Free LLM Safety Guardrail Shieldgemma: Generative ai content moderation based on gemma,

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-07-08T10:04:52.361355Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-07-08T10:00:02.677030Z digest=sha256:90084e959c91c6dc36ebfa9877daee338f6fef2cfed4788237ac452c7e3451e7

Observation 6e1f112c-b9a3-4a0a-9071-e84e501b5dce · outbound

This paper cites ShieldGemma: Generative AI Content Moderation Based on Gemma.

DT-Guard: Intent-Driven Reasoning-Active Training for Reasoning-Free LLM Safety Guardrail ShieldGemma: Generative AI Content Moderation Based on Gemma

Reference 9

Resolution
verified exact
local_arxiv, observed 2026-07-08T10:04:51.428087Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-07-08T10:00:02.677030Z digest=sha256:1aa3bbd4a2e94b646b5e40c6b0e6b9ac763a9dd0cd6ed1012bbc986d3f0cf3ea

Observation 33f58612-2cd1-4783-bbab-edb5e84dd497 · outbound

This paper cites Qwen3Guard Technical Report.

DT-Guard: Intent-Driven Reasoning-Active Training for Reasoning-Free LLM Safety Guardrail Qwen3Guard Technical Report

Reference 10

Resolution
verified exact
local_arxiv, observed 2026-07-08T10:04:51.438848Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-07-08T10:00:02.677030Z digest=sha256:20b43462365ef7ca3fd1d67271abb2eadd8b39f7912fef44c24a2848ad6c558d

Observation 432ad866-d66f-47de-b226-3a7a4636d059 · outbound

This paper cites Yufeng-xguard: A reasoning-centric, interpretable, and flexible guardrail model for large language models, 2026.

DT-Guard: Intent-Driven Reasoning-Active Training for Reasoning-Free LLM Safety Guardrail Yufeng-xguard: A reasoning-centric, interpretable, and flexible guardrail model for large language models, 2026

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-07-08T10:04:52.364558Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-07-08T10:00:02.677030Z digest=sha256:4d222e39ecf71301ab8d619aa3849be70f221eefd51acfc4ada7abfd35819aa2

Observation 5eb61755-d7b1-40cf-92ce-9670233dc6cb · outbound

This paper cites AEGIS: Online Adaptive AI Content Safety Moderation with Ensemble of LLM Experts.

DT-Guard: Intent-Driven Reasoning-Active Training for Reasoning-Free LLM Safety Guardrail AEGIS: Online Adaptive AI Content Safety Moderation with Ensemble of LLM Experts

Reference 12

Resolution
verified exact
local_arxiv, observed 2026-07-08T10:04:51.444702Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-07-08T10:00:02.677030Z digest=sha256:7d358bba43fecd6abf77284a17f07f29ce59253ea7d4774a0c7e0da369aefeb4

Observation 569a6a41-d55b-4fb5-804a-cdbff096b59a · outbound

This paper cites Wildguard: Open one-stop moderation tools for safety risks, jailbreaks, and refusals of llms.

DT-Guard: Intent-Driven Reasoning-Active Training for Reasoning-Free LLM Safety Guardrail Wildguard: Open one-stop moderation tools for safety risks, jailbreaks, and refusals of llms

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-07-08T10:04:52.390756Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-07-08T10:00:02.677030Z digest=sha256:f6479089564785d1451f9fa16f1020fbec9d0b4212028d568ceaf7403b94a1d9

Observation c2c96ca1-9bcf-44a2-bfae-294d9b3a95d3 · outbound

This paper cites PolyGuard: A Multilingual Safety Moderation Tool for 17 Languages.

DT-Guard: Intent-Driven Reasoning-Active Training for Reasoning-Free LLM Safety Guardrail PolyGuard: A Multilingual Safety Moderation Tool for 17 Languages

Reference 14

Resolution
verified exact
local_arxiv, observed 2026-07-08T10:04:51.410268Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-07-08T10:00:02.677030Z digest=sha256:d505018e7e1c9a94ebba759200d99b9ad97e165a4b434c67f94fc8d627b1a6a2

Observation 89d30831-1b5d-4210-8782-5bdf095841ab · outbound

This paper cites Mitigating Jailbreaks with Intent-Aware LLMs.

DT-Guard: Intent-Driven Reasoning-Active Training for Reasoning-Free LLM Safety Guardrail Mitigating Jailbreaks with Intent-Aware LLMs

Reference 15

Resolution
verified exact
local_arxiv, observed 2026-07-08T10:04:51.403792Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-07-08T10:00:02.677030Z digest=sha256:0b169dc31252b256810555f0f610898033700f53bdf3e213a1f1dcb13ea36e09

Observation 0546fb19-ec21-491f-9b17-82aa14b457ba · outbound

This paper cites Dagher, and Haohan Wang.

DT-Guard: Intent-Driven Reasoning-Active Training for Reasoning-Free LLM Safety Guardrail Dagher, and Haohan Wang

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-07-08T10:04:52.387411Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-07-08T10:00:02.677030Z digest=sha256:f9de02bb37568ea583c6270aacb0befa460cc9a8b2707c75e88255a2c89ed978

Observation c252a27a-6eae-4d21-b9b7-5ac90df4be36 · outbound

This paper cites Li, Hui Xiong, and Bryan Hooi.

DT-Guard: Intent-Driven Reasoning-Active Training for Reasoning-Free LLM Safety Guardrail Li, Hui Xiong, and Bryan Hooi

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-07-08T10:04:52.381099Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-07-08T10:00:02.677030Z digest=sha256:23b842787337eb44da361e592ba6d8fb9fdad92c9053fa85f32396493c8ab471

Observation 0d9843e8-bf2c-4f7c-be64-d5c7a6530f08 · outbound

This paper cites Training language models to follow instructions with human feedback.

DT-Guard: Intent-Driven Reasoning-Active Training for Reasoning-Free LLM Safety Guardrail Training language models to follow instructions with human feedback

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-07-08T10:04:52.384437Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-07-08T10:00:02.677030Z digest=sha256:88468b00602f6c4b5b78a4edc0137bf7a403003e30e3debdefa3851971ff3e31

Observation 74af8a97-7b15-4a7b-b4db-74e6f9f6af80 · outbound

This paper cites Constitu- tional ai: Harmlessness from ai feedback, 2022.

DT-Guard: Intent-Driven Reasoning-Active Training for Reasoning-Free LLM Safety Guardrail Constitu- tional ai: Harmlessness from ai feedback, 2022

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-07-08T10:04:52.374572Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-07-08T10:00:02.677030Z digest=sha256:3f4219a4047fbb08e7ed58fe2979e4802ccf78caa5b9549399e46322d5afc235

Observation 167e2297-b225-4f07-8ea7-105d38b86c8f · outbound

This paper cites Direct preference optimization: Your language model is secretly a reward model.

DT-Guard: Intent-Driven Reasoning-Active Training for Reasoning-Free LLM Safety Guardrail Direct preference optimization: Your language model is secretly a reward model

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-07-08T10:04:52.377911Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-07-08T10:00:02.677030Z digest=sha256:51df5bcc1dcf7e9dbaa1d939d0fa3969738c9d4671bd7aedd0f125e79487e21f

Pith citing papers

No inbound Pith citation observations are available.