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Paper Citation Record · LEDGER

Towards AI-$45^{\circ}$ Law: A Roadmap to Trustworthy AGI

As of 21 August 2026, this Paper Citation Record lists 100 of 102 outbound references and 1 inbound Pith citation observation for arXiv:2412.14186.

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

pith.paper-citation-record.v1
2412.14186 v2

Coverage vector

measured 100 of 102 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T20:13:07.507975Z

measured 101 of 101 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-01T16:21:29.283270Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

100 of 102 outbound references displayed

  • verified exact0
  • verified fuzzy17
  • unresolved82
  • parse uncertain0
  • malformed identifier1
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External citation measurements

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Outbound references

Observation ab8e546e-e28e-4db1-a330-e76a9a2fc606 · outbound

This paper cites https://www.anthropic.com/news/anthropics-responsible-scaling- policy, 2023.

Towards AI-$45^{\circ}$ Law: A Roadmap to Trustworthy AGI https://www.anthropic.com/news/anthropics-responsible-scaling- policy, 2023

Reference 1

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Observation 41a2263c-de56-42e9-87ed-9ead3dc8aa32 · outbound

This paper cites https://idais.ai/dialogue/idais- beijing/, 2024.

Towards AI-$45^{\circ}$ Law: A Roadmap to Trustworthy AGI https://idais.ai/dialogue/idais- beijing/, 2024

Reference 2

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Observation 58a51031-9896-4d7e-b7fd-35b6c2fd46ed · outbound

This paper cites https://idais.ai/dialogue/idais-venice/, 2024.

Towards AI-$45^{\circ}$ Law: A Roadmap to Trustworthy AGI https://idais.ai/dialogue/idais-venice/, 2024

Reference 3

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Observation 2bbdeecb-1309-4a0c-a253-0c0c4e33fdec · outbound

This paper cites https://assets.anthropic.com/m/24a47b00f10301cd/original/Anthropic- Responsible-Scaling-Policy-2024-10-15.pdf, 2024.

Towards AI-$45^{\circ}$ Law: A Roadmap to Trustworthy AGI https://assets.anthropic.com/m/24a47b00f10301cd/original/Anthropic- Responsible-Scaling-Policy-2024-10-15.pdf, 2024

Reference 4

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Observation 281d96d5-9922-4d53-a73a-8a28f39c054e · outbound

This paper cites Current state of LLM Risks and AI Guardrails.

Towards AI-$45^{\circ}$ Law: A Roadmap to Trustworthy AGI Current state of LLM Risks and AI Guardrails

Reference 5

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Observation b8bd7614-50ff-4f65-a2e4-d3031ca986b5 · outbound

This paper cites Qwen Technical Report.

Towards AI-$45^{\circ}$ Law: A Roadmap to Trustworthy AGI Qwen Technical Report

Reference 6

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Observation 0b5b63e3-ae89-405e-a6ee-2628632694fa · outbound

This paper cites Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond.

Towards AI-$45^{\circ}$ Law: A Roadmap to Trustworthy AGI Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond

Reference 7

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Observation d221283d-5433-4938-852d-3fecd7b36ac9 · outbound

This paper cites Constitutional AI: Harmlessness from AI Feedback.

Towards AI-$45^{\circ}$ Law: A Roadmap to Trustworthy AGI Constitutional AI: Harmlessness from AI Feedback

Reference 8

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Observation 5e850713-c1f6-4d4d-b0eb-b24d1e45cd17 · outbound

This paper cites Managing extreme ai risks amid rapid progress.

Towards AI-$45^{\circ}$ Law: A Roadmap to Trustworthy AGI Managing extreme ai risks amid rapid progress

Reference 9

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Observation 889594c5-99e1-4e59-9fdc-cd5782c82624 · outbound

This paper cites Mechanistic Interpretability for AI Safety -- A Review.

Towards AI-$45^{\circ}$ Law: A Roadmap to Trustworthy AGI Mechanistic Interpretability for AI Safety -- A Review

Reference 10

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Observation 63d28da4-a34e-4318-afa3-1f03d83a820b · outbound

This paper cites Diverse and effective red teaming with auto-generated rewards and multi-step reinforcement learning.

Towards AI-$45^{\circ}$ Law: A Roadmap to Trustworthy AGI Diverse and effective red teaming with auto-generated rewards and multi-step reinforcement learning

Reference 11

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Observation 236f959f-c4e5-4f57-8810-375533c6a15a · outbound

This paper cites Measuring Progress on Scalable Oversight for Large Language Models.

Towards AI-$45^{\circ}$ Law: A Roadmap to Trustworthy AGI Measuring Progress on Scalable Oversight for Large Language Models

Reference 12

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Observation bdbfbfe4-37dc-4e76-ac13-77a5baf7e6d3 · outbound

This paper cites Language Models are Few-Shot Learners.

Towards AI-$45^{\circ}$ Law: A Roadmap to Trustworthy AGI Language Models are Few-Shot Learners

Reference 13

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Observation 63e58e1d-7919-4a8f-9c68-74d2bba1f73d · outbound

This paper cites The Malicious Use of Artificial Intelligence: Forecasting, Prevention, and Mitigation.

Towards AI-$45^{\circ}$ Law: A Roadmap to Trustworthy AGI The Malicious Use of Artificial Intelligence: Forecasting, Prevention, and Mitigation

Reference 14

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Observation 262f3c42-fa6c-49ab-a53a-dad64ce2a799 · outbound

This paper cites Weak-to-Strong Generalization: Eliciting Strong Capabilities With Weak Supervision.

Towards AI-$45^{\circ}$ Law: A Roadmap to Trustworthy AGI Weak-to-Strong Generalization: Eliciting Strong Capabilities With Weak Supervision

Reference 15

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Observation b83562e4-d564-4e7d-816c-bc01df2926fa · outbound

This paper cites InternLM2 Technical Report.

Towards AI-$45^{\circ}$ Law: A Roadmap to Trustworthy AGI InternLM2 Technical Report

Reference 16

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Observation 54a3d488-2459-4103-bab2-60d6ee1f6309 · outbound

This paper cites Extracting training data from large language models.

Towards AI-$45^{\circ}$ Law: A Roadmap to Trustworthy AGI Extracting training data from large language models

Reference 17

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Observation 28ee7580-0ebe-4f16-8a2b-135b98a23351 · outbound

This paper cites Is Power-Seeking AI an Existential Risk?.

Towards AI-$45^{\circ}$ Law: A Roadmap to Trustworthy AGI Is Power-Seeking AI an Existential Risk?

Reference 18

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Observation f759c302-4a0f-4278-a65f-33b9d4d1fef2 · outbound

This paper cites Quantifying and mitigating unimodal biases in multimodal large language models: A causal perspective.

Towards AI-$45^{\circ}$ Law: A Roadmap to Trustworthy AGI Quantifying and mitigating unimodal biases in multimodal large language models: A causal perspective

Reference 19

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Observation 60224cab-b03b-4c4d-96d3-6579563faebe · outbound

This paper cites Cello: Causal evaluation of large vision- language models.

Towards AI-$45^{\circ}$ Law: A Roadmap to Trustworthy AGI Cello: Causal evaluation of large vision- language models

Reference 20

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Observation 2d6b7c5d-e106-480c-8717-670a368b630e · outbound

This paper cites From Imitation to Introspection: Probing Self-Consciousness in Language Models.

Towards AI-$45^{\circ}$ Law: A Roadmap to Trustworthy AGI From Imitation to Introspection: Probing Self-Consciousness in Language Models

Reference 21

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Observation 629e536e-6ea7-4671-beca-a0e13956bd71 · outbound

This paper cites Internvl: Scaling up vision foundation models and aligning for generic visual-linguistic tasks.

Towards AI-$45^{\circ}$ Law: A Roadmap to Trustworthy AGI Internvl: Scaling up vision foundation models and aligning for generic visual-linguistic tasks

Reference 22

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Observation b229e7d4-f9f5-411b-853e-31bbf6c9f522 · outbound

This paper cites Feder Cooper, Christopher A.

Towards AI-$45^{\circ}$ Law: A Roadmap to Trustworthy AGI Feder Cooper, Christopher A

Reference 23

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Observation c4b76f71-7b68-47b2-b794-bb5d58aa89d8 · outbound

This paper cites Towards Guaranteed Safe AI: A Framework for Ensuring Robust and Reliable AI Systems.

Towards AI-$45^{\circ}$ Law: A Roadmap to Trustworthy AGI Towards Guaranteed Safe AI: A Framework for Ensuring Robust and Reliable AI Systems

Reference 24

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Observation 1496d89d-e536-41f9-99df-c3d4439a4620 · outbound

This paper cites Arti- ficial intelligence regulation: a framework for governance.

Towards AI-$45^{\circ}$ Law: A Roadmap to Trustworthy AGI Arti- ficial intelligence regulation: a framework for governance

Reference 25

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Observation b97befef-d27a-4dd4-91b3-a84e2eacb63d · outbound

This paper cites Fine-Tuning Pretrained Language Models: Weight Initializations, Data Orders, and Early Stopping.

Towards AI-$45^{\circ}$ Law: A Roadmap to Trustworthy AGI Fine-Tuning Pretrained Language Models: Weight Initializations, Data Orders, and Early Stopping

Reference 26

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Observation c3c68b53-5315-4ccd-bdb0-d1e3ded9c867 · outbound

This paper cites InternLM-XComposer2: Mastering Free-form Text-Image Composition and Comprehension in Vision-Language Large Model.

Towards AI-$45^{\circ}$ Law: A Roadmap to Trustworthy AGI InternLM-XComposer2: Mastering Free-form Text-Image Composition and Comprehension in Vision-Language Large Model

Reference 27

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Observation 96721cf1-8b99-466c-9273-56eeb7809bef · outbound

This paper cites Attacks, Defenses and Evaluations for LLM Conversation Safety: A Survey.

Towards AI-$45^{\circ}$ Law: A Roadmap to Trustworthy AGI Attacks, Defenses and Evaluations for LLM Conversation Safety: A Survey

Reference 28

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Observation f6c775fd-b12e-4977-90d1-3386ab554974 · outbound

This paper cites CLEAR: Character Unlearning in Textual and Visual Modalities.

Towards AI-$45^{\circ}$ Law: A Roadmap to Trustworthy AGI CLEAR: Character Unlearning in Textual and Visual Modalities

Reference 29

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Observation c5821417-8506-4f86-916a-e7ae49a6dc5a · outbound

This paper cites The Llama 3 Herd of Models.

Towards AI-$45^{\circ}$ Law: A Roadmap to Trustworthy AGI The Llama 3 Herd of Models

Reference 30

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Observation 68ab911b-f204-43f1-b53c-a0627c33c8fe · outbound

This paper cites Who's Harry Potter? Approximate Unlearning in LLMs.

Towards AI-$45^{\circ}$ Law: A Roadmap to Trustworthy AGI Who's Harry Potter? Approximate Unlearning in LLMs

Reference 31

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Observation a34283bd-422d-4cda-9ea6-f68ba01fcd37 · outbound

This paper cites Statement on ai risk, 2024.

Towards AI-$45^{\circ}$ Law: A Roadmap to Trustworthy AGI Statement on ai risk, 2024

Reference 32

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Observation 9a212e10-a178-46d7-9d30-e1f3253a6bc1 · outbound

This paper cites Counterintuitive behavior of social systems.

Towards AI-$45^{\circ}$ Law: A Roadmap to Trustworthy AGI Counterintuitive behavior of social systems

Reference 33

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Observation e9f78bdb-adc2-4a7c-9db6-765f087e1b8c · outbound

This paper cites Artificial intelligence, values, and alignment.

Towards AI-$45^{\circ}$ Law: A Roadmap to Trustworthy AGI Artificial intelligence, values, and alignment

Reference 34

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Observation 44781c90-f85b-42dc-bbc7-0255d4a181d8 · outbound

This paper cites Mental models.

Towards AI-$45^{\circ}$ Law: A Roadmap to Trustworthy AGI Mental models

Reference 35

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Observation 5c6463b0-eb65-496e-b44b-07a88f24e229 · outbound

This paper cites Mllmguard: A multi-dimensional safety evaluation suite for multimodal large language models, 2024.

Towards AI-$45^{\circ}$ Law: A Roadmap to Trustworthy AGI Mllmguard: A multi-dimensional safety evaluation suite for multimodal large language models, 2024

Reference 36

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Observation e355bb79-0c2d-48c1-93f1-45c9bcbf154d · outbound

This paper cites Recurrent world models facilitate policy evolution.

Towards AI-$45^{\circ}$ Law: A Roadmap to Trustworthy AGI Recurrent world models facilitate policy evolution

Reference 37

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Observation c4c07748-652f-45fb-98d3-c01ae984de9b · outbound

This paper cites An Overview of Catastrophic AI Risks.

Towards AI-$45^{\circ}$ Law: A Roadmap to Trustworthy AGI An Overview of Catastrophic AI Risks

Reference 38

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Observation 54134020-7c5e-4841-8da0-db7ab7cff9b9 · outbound

This paper cites Stabilizing translucencies: Governing ai transparency by standardization.

Towards AI-$45^{\circ}$ Law: A Roadmap to Trustworthy AGI Stabilizing translucencies: Governing ai transparency by standardization

Reference 39

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Observation b2d6cd27-a09b-40b7-ab78-1cee5c703f99 · outbound

This paper cites Curiosity-driven Red-teaming for Large Language Models.

Towards AI-$45^{\circ}$ Law: A Roadmap to Trustworthy AGI Curiosity-driven Red-teaming for Large Language Models

Reference 40

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Observation 80aa5f79-19da-4647-bd0e-e171fa565044 · outbound

This paper cites Flames: Benchmarking Value Alignment of LLMs in Chinese.

Towards AI-$45^{\circ}$ Law: A Roadmap to Trustworthy AGI Flames: Benchmarking Value Alignment of LLMs in Chinese

Reference 41

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Observation 89137e52-1153-4bc3-86f2-d01a364fb5b4 · outbound

This paper cites From pixels to principles: A decade of progress and landscape in trustworthy computer vision.

Towards AI-$45^{\circ}$ Law: A Roadmap to Trustworthy AGI From pixels to principles: A decade of progress and landscape in trustworthy computer vision

Reference 42

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Observation 8523b380-a40f-4292-8cba-5ff8b12a510b · outbound

This paper cites TrustLLM: Trustworthiness in Large Language Models.

Towards AI-$45^{\circ}$ Law: A Roadmap to Trustworthy AGI TrustLLM: Trustworthiness in Large Language Models

Reference 43

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source=pdf_text observed=2026-08-11T20:13:07.216141Z digest=sha256:722f71c49e0683c21409e8679904f612f0f1839289af0c9534ff6956ecc7bf5d

Observation edb1d758-75ab-4852-9981-5c1c3e923e19 · outbound

This paper cites When code isn’t law: rethinking regulation for artificial intelligence.

Towards AI-$45^{\circ}$ Law: A Roadmap to Trustworthy AGI When code isn’t law: rethinking regulation for artificial intelligence

Reference 44

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source=pdf_text observed=2026-08-11T20:13:07.220945Z digest=sha256:1c4bef9695389d5e16d96a5128a4b4ed88af30a74607754aa3d7fecca46e64ec

Observation 283c55fa-0836-4387-b2f3-17ca69c13622 · outbound

This paper cites Scaling Laws for Neural Language Models.

Towards AI-$45^{\circ}$ Law: A Roadmap to Trustworthy AGI Scaling Laws for Neural Language Models

Reference 45

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source=pdf_text observed=2026-08-11T20:13:07.226223Z digest=sha256:c43947e4b4edb1bcf9d45698951535fcf1a72b7ec2ea4d6e8a6b21101c074bb9

Observation 5f54af0a-9567-42a7-a19a-72673ac5eb22 · outbound

This paper cites Aligning Large Language Models with Representation Editing: A Control Perspective.

Towards AI-$45^{\circ}$ Law: A Roadmap to Trustworthy AGI Aligning Large Language Models with Representation Editing: A Control Perspective

Reference 46

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source=pdf_text observed=2026-08-11T20:13:07.232030Z digest=sha256:d8f3157b8ca8c53e3c31339577a92696e23d5be93da27e2cd2f0022652f48c44

Observation 9d5529e7-ddff-4b71-b5e3-91683dd7df83 · outbound

This paper cites Evaluations: autonomy and artificial intelligence: a threat or savior? Springer, 2017.

Towards AI-$45^{\circ}$ Law: A Roadmap to Trustworthy AGI Evaluations: autonomy and artificial intelligence: a threat or savior? Springer, 2017

Reference 47

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source=pdf_text observed=2026-08-11T20:13:07.236725Z digest=sha256:00e249a719363c887f02aae034bb1ccdb540f2ebc61feb18b7af4a594a5a5334

Observation 8444ec68-984f-4367-8dab-ce953c9145a2 · outbound

This paper cites Learning to watermark llm-generated text via rein- forcement learning.

Towards AI-$45^{\circ}$ Law: A Roadmap to Trustworthy AGI Learning to watermark llm-generated text via rein- forcement learning

Reference 48

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source=pdf_text observed=2026-08-11T20:13:07.240829Z digest=sha256:f5dcca7320d8b442b085213bf22cdc704842081389537e95a19906eae05d0c86

Observation 00fdb958-fd79-4e4b-acbc-1649665b3082 · outbound

This paper cites Deepfakes, phrenology, surveillance, and more! a taxonomy of ai privacy risks.

Towards AI-$45^{\circ}$ Law: A Roadmap to Trustworthy AGI Deepfakes, phrenology, surveillance, and more! a taxonomy of ai privacy risks

Reference 49

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source=pdf_text observed=2026-08-11T20:13:07.244839Z digest=sha256:aff872b15de1435e9f54fca68ad8e72e17857d772857cab5336685ecbb10ea29

Observation e68eff2c-9636-462c-9957-a9c9d94546de · outbound

This paper cites Trustworthy ai: From principles to practices.

Towards AI-$45^{\circ}$ Law: A Roadmap to Trustworthy AGI Trustworthy ai: From principles to practices

Reference 50

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source=pdf_text observed=2026-08-11T20:13:07.251036Z digest=sha256:4bba3f58f1cfc3c99efc19c115851559f24d0d68f61128ddf1be49e3249ef104

Observation d7e39809-8f23-4808-b418-51f7bb2a7b08 · outbound

This paper cites Inference- time intervention: Eliciting truthful answers from a language model.

Towards AI-$45^{\circ}$ Law: A Roadmap to Trustworthy AGI Inference- time intervention: Eliciting truthful answers from a language model

Reference 51

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Observation 42ba8dac-baab-4d56-93c4-e2db98710fb7 · outbound

This paper cites SALAD-Bench: A Hierarchical and Comprehensive Safety Benchmark for Large Language Models.

Towards AI-$45^{\circ}$ Law: A Roadmap to Trustworthy AGI SALAD-Bench: A Hierarchical and Comprehensive Safety Benchmark for Large Language Models

Reference 52

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source=pdf_text observed=2026-08-11T20:13:07.261539Z digest=sha256:d85bb46609f74e8addc4eef197f37a135cd3cce4738b2992aaaf5b7140158895

Observation 1b155ab8-2e38-4823-8f44-c8995285353c · outbound

This paper cites Controllable Text Generation for Large Language Models: A Survey.

Towards AI-$45^{\circ}$ Law: A Roadmap to Trustworthy AGI Controllable Text Generation for Large Language Models: A Survey

Reference 53

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source=pdf_text observed=2026-08-11T20:13:07.267089Z digest=sha256:86c6bf197c122ca14ce6be2a196305642d6cbf9a0fc334b57b9e2c5b6fbf8a4c

Observation 07a52096-c47a-4aad-b372-5ec55040a17f · outbound

This paper cites A survey of text watermarking in the era of large language models.

Towards AI-$45^{\circ}$ Law: A Roadmap to Trustworthy AGI A survey of text watermarking in the era of large language models

Reference 54

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source=pdf_text observed=2026-08-11T20:13:07.271704Z digest=sha256:9cac1a140ab2dbdce2380986159ea89e96fdf318371c7d5d355538dda37871fa

Observation c7eb4a8b-0692-4ed1-b7fe-0adecf89127b · outbound

This paper cites Don’t always say no to me: Benchmarking safety-related refusal in large vlm.

Towards AI-$45^{\circ}$ Law: A Roadmap to Trustworthy AGI Don’t always say no to me: Benchmarking safety-related refusal in large vlm

Reference 55

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source=pdf_text observed=2026-08-11T20:13:07.277124Z digest=sha256:a24e1db312da6c800b71f7154f406f4da34870fef620083b1e7333e37bea90c4

Observation 1271534e-75c2-479f-abdd-6aff9529ade7 · outbound

This paper cites Mm-safetybench: A benchmark for safety evaluation of multimodal large language models.

Towards AI-$45^{\circ}$ Law: A Roadmap to Trustworthy AGI Mm-safetybench: A benchmark for safety evaluation of multimodal large language models

Reference 56

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Observation f65490ca-8a6c-4ca7-9769-7301d70a9cfd · outbound

This paper cites MM-SafetyBench: A Benchmark for Safety Evaluation of Multimodal Large Language Models.

Towards AI-$45^{\circ}$ Law: A Roadmap to Trustworthy AGI MM-SafetyBench: A Benchmark for Safety Evaluation of Multimodal Large Language Models

Reference 57

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source=pdf_text observed=2026-08-11T20:13:07.291865Z digest=sha256:8bbb950bd885ea8ef2bc6091b0ae124b43d0a8986430302d4b712a5b041b1c54

Observation 689e8dc2-d173-4654-887a-6c7d80f166a7 · outbound

This paper cites Trustworthy LLMs: a Survey and Guideline for Evaluating Large Language Models' Alignment.

Towards AI-$45^{\circ}$ Law: A Roadmap to Trustworthy AGI Trustworthy LLMs: a Survey and Guideline for Evaluating Large Language Models' Alignment

Reference 58

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source=pdf_text observed=2026-08-11T20:13:07.298334Z digest=sha256:9e2e86a3680a93f92380ff44b9d06b59ef271cb03511b42dd7e328fea9675a52

Observation 05e04c1e-0eae-4277-8747-463fc9acd83c · outbound

This paper cites Machine Unlearning in Generative AI: A Survey.

Towards AI-$45^{\circ}$ Law: A Roadmap to Trustworthy AGI Machine Unlearning in Generative AI: A Survey

Reference 59

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source=pdf_text observed=2026-08-11T20:13:07.303723Z digest=sha256:8ae871985593d63e1465e8fa1d0ab3810e39a3f744e5b14362eb49d35b26b187

Observation 23e6973a-ccf5-44ce-9459-5c0cec0f506e · outbound

This paper cites Inference-Time Language Model Alignment via Integrated Value Guidance.

Towards AI-$45^{\circ}$ Law: A Roadmap to Trustworthy AGI Inference-Time Language Model Alignment via Integrated Value Guidance

Reference 60

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Observation f31435b5-8348-4a73-8175-d677027295e4 · outbound

This paper cites Causal interpretability for machine learning-problems, methods and evaluation.

Towards AI-$45^{\circ}$ Law: A Roadmap to Trustworthy AGI Causal interpretability for machine learning-problems, methods and evaluation

Reference 61

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source=pdf_text observed=2026-08-11T20:13:07.315926Z digest=sha256:e3faf6a94975b69bf3c9cf89b43b57f21f32836a3cbc56c1c658202993cd2c39

Observation 55a5e382-a4d6-405a-a976-34a5494ab796 · outbound

This paper cites Large Language Models in Cybersecurity: State-of-the-Art.

Towards AI-$45^{\circ}$ Law: A Roadmap to Trustworthy AGI Large Language Models in Cybersecurity: State-of-the-Art

Reference 62

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source=pdf_text observed=2026-08-11T20:13:07.320538Z digest=sha256:3861c8c596dd892de68d2bc5712027e3f1efa43f2aa7e520a71868ba42f8b8fa

Observation 7be1af07-4abb-4b01-a920-0ab8dbe4f85d · outbound

This paper cites Rule Based Rewards for Language Model Safety.

Towards AI-$45^{\circ}$ Law: A Roadmap to Trustworthy AGI Rule Based Rewards for Language Model Safety

Reference 63

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source=pdf_text observed=2026-08-11T20:13:07.325631Z digest=sha256:d9bd7a62607d0869aef21cd873b841479a987f09e8e816ecafd99cb6db3c9115

Observation 524aa9ec-29a2-45c5-a1c0-3a4c0dd07805 · outbound

This paper cites Accountability in artificial intelligence: what it is and how it works.

Towards AI-$45^{\circ}$ Law: A Roadmap to Trustworthy AGI Accountability in artificial intelligence: what it is and how it works

Reference 64

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source=pdf_text observed=2026-08-11T20:13:07.330151Z digest=sha256:3370a67cdc669e77688e4d2816656e62aba8faac6190d4bc7fef3a2b98f1dfcd

Observation 195be6b6-8310-443f-ae8f-c415c63e20a0 · outbound

This paper cites UniGuard: Towards Universal Safety Guardrails for Jailbreak Attacks on Multimodal Large Language Models.

Towards AI-$45^{\circ}$ Law: A Roadmap to Trustworthy AGI UniGuard: Towards Universal Safety Guardrails for Jailbreak Attacks on Multimodal Large Language Models

Reference 65

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Observation 676e3913-809f-4b4b-9c04-dc6baecc17a9 · outbound

This paper cites GPT-4 technical report.

Towards AI-$45^{\circ}$ Law: A Roadmap to Trustworthy AGI GPT-4 technical report

Reference 66

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source=pdf_text observed=2026-08-11T20:13:07.338735Z digest=sha256:f4bc8a4d68532df98c6b23918747ac232f5a71abd19e69c8e9f91bd525d7ead5

Observation c75a379a-39c4-4b3f-921f-36f0185ce1e3 · outbound

This paper cites Openai o1 system card, 2024.

Towards AI-$45^{\circ}$ Law: A Roadmap to Trustworthy AGI Openai o1 system card, 2024

Reference 67

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source=pdf_text observed=2026-08-11T20:13:07.343050Z digest=sha256:a958cdb5e11997f8111716084299f62fc5a7d60a5d8487399f14f6039765aad5

Observation c3837409-4563-4be1-a293-d69f35d01da3 · outbound

This paper cites Video generation models as world simulators, 2024.

Towards AI-$45^{\circ}$ Law: A Roadmap to Trustworthy AGI Video generation models as world simulators, 2024

Reference 68

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source=pdf_text observed=2026-08-11T20:13:07.347945Z digest=sha256:036c0871467854d47a41fb49c1986cd6847c26ac3addaea766f2ac1ff1d9a4aa

Observation 17ad1dea-471c-480c-bb83-b909736bb710 · outbound

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

Towards AI-$45^{\circ}$ Law: A Roadmap to Trustworthy AGI Training language models to follow instructions with human feedback

Reference 69

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source=pdf_text observed=2026-08-11T20:13:07.351732Z digest=sha256:a700d6dd719e4786a13ba78e64556c64acfe565a8da03c6b4265bd8a743bf53f

Observation 60f9a0a0-f821-48ab-9bf8-86c3c2de378c · outbound

This paper cites A ‘biased’emerging governance regime for artificial intelligence? how ai ethics get skewed moving from principles to practices.

Towards AI-$45^{\circ}$ Law: A Roadmap to Trustworthy AGI A ‘biased’emerging governance regime for artificial intelligence? how ai ethics get skewed moving from principles to practices

Reference 70

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source=pdf_text observed=2026-08-11T20:13:07.362510Z digest=sha256:ac9bbebd3ad0de323576ca1b830c1256d96018e49c82a206fe281bd1ef28b4d1

Observation b3aed9a6-5a73-4d0f-83ed-d4ab18aae8be · outbound

This paper cites Automatically Correcting Large Language Models: Surveying the landscape of diverse self-correction strategies.

Towards AI-$45^{\circ}$ Law: A Roadmap to Trustworthy AGI Automatically Correcting Large Language Models: Surveying the landscape of diverse self-correction strategies

Reference 71

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source=pdf_text observed=2026-08-11T20:13:07.366906Z digest=sha256:6fb61beabd1d1f54fb71cfa8bf0b05ef64c25debbeac413c9346eba408e70433

Observation e19c3bd3-579c-4dab-a6c1-ee7d5237ce5c · outbound

This paper cites Automated Red Teaming with GOAT: the Generative Offensive Agent Tester.

Towards AI-$45^{\circ}$ Law: A Roadmap to Trustworthy AGI Automated Red Teaming with GOAT: the Generative Offensive Agent Tester

Reference 72

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source=pdf_text observed=2026-08-11T20:13:07.373813Z digest=sha256:a6354b56f1ce13ee419a31edc1c72a8a5294c45341f00bbc56f242fa4079dd93

Observation f16bb05c-2e1e-434b-85ec-fc4e2aa33710 · outbound

This paper cites Causality.

Towards AI-$45^{\circ}$ Law: A Roadmap to Trustworthy AGI Causality

Reference 73

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source=pdf_text observed=2026-08-11T20:13:07.378160Z digest=sha256:9779986d177ba2b352556935432b5de1f6f24db0350a0c190bc7e670b64e4ba2

Observation c8f76e6e-35a8-417c-97d3-025aaf4dc9f2 · outbound

This paper cites The book of why: the new science of cause and effect.

Towards AI-$45^{\circ}$ Law: A Roadmap to Trustworthy AGI The book of why: the new science of cause and effect

Reference 74

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Observation 769713d2-1ffc-4ad1-acfa-1bd846349a73 · outbound

This paper cites Red Teaming Language Models with Language Models.

Towards AI-$45^{\circ}$ Law: A Roadmap to Trustworthy AGI Red Teaming Language Models with Language Models

Reference 75

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Observation 39e9f853-911d-49f4-b09d-55b6d9e1dc19 · outbound

This paper cites The Tug of War Within: Mitigating the Fairness-Privacy Conflicts in Large Language Models.

Towards AI-$45^{\circ}$ Law: A Roadmap to Trustworthy AGI The Tug of War Within: Mitigating the Fairness-Privacy Conflicts in Large Language Models

Reference 76

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Observation d15e6ae2-5b79-456d-a11f-6de72e10181c · outbound

This paper cites Towards Tracing Trustworthiness Dynamics: Revisiting Pre-training Period of Large Language Models.

Towards AI-$45^{\circ}$ Law: A Roadmap to Trustworthy AGI Towards Tracing Trustworthiness Dynamics: Revisiting Pre-training Period of Large Language Models

Reference 77

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source=pdf_text observed=2026-08-11T20:13:07.396643Z digest=sha256:3c4a0235d64da92e8c5cc8d69060e5a6cf53922d6ab78507bddd26b43b22c261

Observation 49771c48-993c-4447-9870-c923c6743ed1 · outbound

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

Towards AI-$45^{\circ}$ Law: A Roadmap to Trustworthy AGI Direct preference optimization: Your language model is secretly a reward model

Reference 78

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Observation 151fcb9d-a2b4-4a70-aac3-00df20dfe079 · outbound

This paper cites Natural language processing: transform- ing how machines understand human language (2023).

Towards AI-$45^{\circ}$ Law: A Roadmap to Trustworthy AGI Natural language processing: transform- ing how machines understand human language (2023)

Reference 79

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source=pdf_text observed=2026-08-11T20:13:07.405843Z digest=sha256:3cc0100df56c1344bb4193c45dae4b687fd7bddfe7951e12e265dea035f94269

Observation ca19857c-496d-4e75-8bdd-b225bedc72f2 · outbound

This paper cites Identifying Semantic Induction Heads to Understand In-Context Learning.

Towards AI-$45^{\circ}$ Law: A Roadmap to Trustworthy AGI Identifying Semantic Induction Heads to Understand In-Context Learning

Reference 80

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source=pdf_text observed=2026-08-11T20:13:07.409981Z digest=sha256:b449fae3d870322019c3b7af935dd948a2f5ffbd597f6e830a5da984f9ffe4aa

Observation 7a9bea55-8d9c-4049-b80a-02e9a47ebd29 · outbound

This paper cites Self-Reflection in LLM Agents: Effects on Problem-Solving Performance.

Towards AI-$45^{\circ}$ Law: A Roadmap to Trustworthy AGI Self-Reflection in LLM Agents: Effects on Problem-Solving Performance

Reference 82

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source=pdf_text observed=2026-08-11T20:13:07.420105Z digest=sha256:9b7f4d8731944e4da6bfadf37569426f920970352fe67e017fa8a97dbdb2dcb2

Observation 6680b5c9-4332-47e4-902b-d10b72e4bf9e · outbound

This paper cites Scaling Laws for Deep Learning.

Towards AI-$45^{\circ}$ Law: A Roadmap to Trustworthy AGI Scaling Laws for Deep Learning

Reference 83

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source=pdf_text observed=2026-08-11T20:13:07.424428Z digest=sha256:3435ca091a005f910a8e27d51527e370c691217aab65112e879f75d4079653bc

Observation 3efea1a6-9bdf-44c0-941e-e8f650ae0132 · outbound

This paper cites Re- flexion: Language agents with verbal reinforcement learning.

Towards AI-$45^{\circ}$ Law: A Roadmap to Trustworthy AGI Re- flexion: Language agents with verbal reinforcement learning

Reference 84

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source=pdf_text observed=2026-08-11T20:13:07.428521Z digest=sha256:cc6a8b150eaf9e2473156b940cb186defc912b99ab6c62b87215426e3c04c95c

Observation 34d9f7ab-1a35-413c-a767-d6663dfcc92e · outbound

This paper cites Learning to summarize with human feedback.

Towards AI-$45^{\circ}$ Law: A Roadmap to Trustworthy AGI Learning to summarize with human feedback

Reference 85

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source=pdf_text observed=2026-08-11T20:13:07.432980Z digest=sha256:95a1ad13e7addfa38c4dd810900cfba0774f0509668f0d31636eb30ed8392194

Observation 23e56d77-ca8f-4a3e-9fd0-98470ed9e8fb · outbound

This paper cites Reinforcement learning: An introduction.

Towards AI-$45^{\circ}$ Law: A Roadmap to Trustworthy AGI Reinforcement learning: An introduction

Reference 86

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source=pdf_text observed=2026-08-11T20:13:07.437265Z digest=sha256:2b1175bd2503df2b94af7e9302f5488851fa4acbba172d865208a09190defd93

Observation 6c44c11f-f240-4c30-97ce-93b98df58aeb · outbound

This paper cites CAT-LLM: Style-enhanced Large Language Models with Text Style Definition for Chinese Article-style Transfer.

Towards AI-$45^{\circ}$ Law: A Roadmap to Trustworthy AGI CAT-LLM: Style-enhanced Large Language Models with Text Style Definition for Chinese Article-style Transfer

Reference 87

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source=pdf_text observed=2026-08-11T20:13:07.441487Z digest=sha256:71ea4410cae6aae6619df5374af488a4e5e388a3bcff48174ddfd6dc539932ef

Observation 17f9e657-7e39-4324-8e44-f4fc91b14386 · outbound

This paper cites Llama 2: Open Foundation and Fine-Tuned Chat Models.

Towards AI-$45^{\circ}$ Law: A Roadmap to Trustworthy AGI Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 88

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Observation bc986fd7-fa04-4f3f-82bf-ac25556e8fea · outbound

This paper cites Value sensitive design and responsible innovation.

Towards AI-$45^{\circ}$ Law: A Roadmap to Trustworthy AGI Value sensitive design and responsible innovation

Reference 89

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source=pdf_text observed=2026-08-11T20:13:07.450736Z digest=sha256:fe48cdf2cde4e3182ea5d87cfb9cb48c8e6fcf0355c37034af1b2ca8e9cedcc3

Observation 35940662-954e-4a70-849f-92b532d02452 · outbound

This paper cites Interpretable counterfactual explanations guided by prototypes.

Towards AI-$45^{\circ}$ Law: A Roadmap to Trustworthy AGI Interpretable counterfactual explanations guided by prototypes

Reference 90

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source=pdf_text observed=2026-08-11T20:13:07.454911Z digest=sha256:4e9053a0e1e7724a26fda75fc853f00949bd8e0dd5aeb81cc5af879681968936

Observation 02a5e747-6ba4-4c50-939a-b2944992cd86 · outbound

This paper cites Counterfactual Explanations and Algorithmic Recourses for Machine Learning: A Review.

Towards AI-$45^{\circ}$ Law: A Roadmap to Trustworthy AGI Counterfactual Explanations and Algorithmic Recourses for Machine Learning: A Review

Reference 91

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Observation 5b9ca466-f652-46ac-9542-edbe4183b4a4 · outbound

This paper cites Decodingtrust: A comprehensive assess- ment of trustworthiness in gpt models.

Towards AI-$45^{\circ}$ Law: A Roadmap to Trustworthy AGI Decodingtrust: A comprehensive assess- ment of trustworthiness in gpt models

Reference 92

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source=pdf_text observed=2026-08-11T20:13:07.465862Z digest=sha256:ca8df5e3fccb3d3c9621e9bd42fed87ad305b2308e63da3ce0ce7cea6afaba17

Observation 1d89373d-94c2-434b-af8d-6d18ed66cf22 · outbound

This paper cites Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution.

Towards AI-$45^{\circ}$ Law: A Roadmap to Trustworthy AGI Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution

Reference 93

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Observation 318432f9-31a9-43b0-a95a-fa2b0538aa85 · outbound

This paper cites Emu3: Next-Token Prediction is All You Need.

Towards AI-$45^{\circ}$ Law: A Roadmap to Trustworthy AGI Emu3: Next-Token Prediction is All You Need

Reference 94

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Observation 44223556-8486-4980-a048-5f8035dd494e · outbound

This paper cites ai safety as global public goods.

Towards AI-$45^{\circ}$ Law: A Roadmap to Trustworthy AGI ai safety as global public goods

Reference 95

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source=pdf_text observed=2026-08-11T20:13:07.480375Z digest=sha256:1de29dc5c11a30a5b8dc8edd74528d5d7c89c3560d3a77ae1a655b699d12d6a8

Observation 7337fddf-e43e-412b-aca7-f4f38d81bc88 · outbound

This paper cites Using the veil of ignorance to align ai systems with principles of justice.

Towards AI-$45^{\circ}$ Law: A Roadmap to Trustworthy AGI Using the veil of ignorance to align ai systems with principles of justice

Reference 96

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source=pdf_text observed=2026-08-11T20:13:07.484432Z digest=sha256:693d48eb1f2138d5b6f2c22d933b055895a75707014d9432979d6a0b765604e1

Observation 44874b7e-63ac-4ab6-acb2-0fa4c39cdb27 · outbound

This paper cites EFUF: Efficient Fine-grained Unlearning Framework for Mitigating Hallucinations in Multimodal Large Language Models.

Towards AI-$45^{\circ}$ Law: A Roadmap to Trustworthy AGI EFUF: Efficient Fine-grained Unlearning Framework for Mitigating Hallucinations in Multimodal Large Language Models

Reference 97

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Observation 30b9adf3-ae9b-40a8-a187-bc28328e9873 · outbound

This paper cites Qwen2 Technical Report.

Towards AI-$45^{\circ}$ Law: A Roadmap to Trustworthy AGI Qwen2 Technical Report

Reference 98

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Observation 79bcf0b3-c09a-4a53-a88e-4b5bb5af8f4a · outbound

This paper cites Huref: Human-readable fingerprint for large language models.

Towards AI-$45^{\circ}$ Law: A Roadmap to Trustworthy AGI Huref: Human-readable fingerprint for large language models

Reference 99

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source=pdf_text observed=2026-08-11T20:13:07.498972Z digest=sha256:d3b1cad57c460fe2cf7dc65aefa3bb85e21085f859e30c088503ca7ab4590e7c

Observation f62cc241-170d-4d78-bebe-41903a85de1f · outbound

This paper cites The Better Angels of Machine Personality: How Personality Relates to LLM Safety.

Towards AI-$45^{\circ}$ Law: A Roadmap to Trustworthy AGI The Better Angels of Machine Personality: How Personality Relates to LLM Safety

Reference 100

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Observation 0ed64c77-9407-45b1-9320-5ba6919573f3 · outbound

This paper cites REEF: Representation Encoding Fingerprints for Large Language Models.

Towards AI-$45^{\circ}$ Law: A Roadmap to Trustworthy AGI REEF: Representation Encoding Fingerprints for Large Language Models

Reference 101

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Pith citing papers

Observation b10ab4f7-b386-4150-b888-57121a19ab40 · inbound

An Early Warning of Emerging Biosecurity Risks in Frontier LLMs cites this paper.

An Early Warning of Emerging Biosecurity Risks in Frontier LLMs Towards AI-$45^{\circ}$ Law: A Roadmap to Trustworthy AGI

Reference 78

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source=pdf_text observed=2026-08-01T16:21:29.283270Z digest=sha256:651dd4f6170aeed01f99a5bb6cc294a6a8bc90c821bdf332b0488b792d14590f