Foundational Challenges in Assuring Alignment and Safety of Large Language Models | Paper Citation Record

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Scaling and renormalization in high-dimensional regression cites this paper.

Scaling and renormalization in high-dimensional regression Foundational Challenges in Assuring Alignment and Safety of Large Language Models

Reference 3

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WildGuard: Open One-Stop Moderation Tools for Safety Risks, Jailbreaks, and Refusals of LLMs cites this paper.

WildGuard: Open One-Stop Moderation Tools for Safety Risks, Jailbreaks, and Refusals of LLMs Foundational Challenges in Assuring Alignment and Safety of Large Language Models

Reference 4

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Can sparse autoencoders be used to decompose and interpret steering vectors? cites this paper.

Can sparse autoencoders be used to decompose and interpret steering vectors? Foundational Challenges in Assuring Alignment and Safety of Large Language Models

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DROJ: A Prompt-Driven Attack against Large Language Models cites this paper.

DROJ: A Prompt-Driven Attack against Large Language Models Foundational Challenges in Assuring Alignment and Safety of Large Language Models

Reference 3

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Llama Guard 3 Vision: Safeguarding Human-AI Image Understanding Conversations cites this paper.

Llama Guard 3 Vision: Safeguarding Human-AI Image Understanding Conversations Foundational Challenges in Assuring Alignment and Safety of Large Language Models

Reference 2015

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Predicting Emergent Capabilities by Finetuning cites this paper.

Predicting Emergent Capabilities by Finetuning Foundational Challenges in Assuring Alignment and Safety of Large Language Models

Reference 4

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Predictable Emergent Abilities of LLMs: Proxy Tasks Are All You Need cites this paper.

Predictable Emergent Abilities of LLMs: Proxy Tasks Are All You Need Foundational Challenges in Assuring Alignment and Safety of Large Language Models

Reference 3

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Neural Scaling Laws Rooted in the Data Distribution cites this paper.

Neural Scaling Laws Rooted in the Data Distribution Foundational Challenges in Assuring Alignment and Safety of Large Language Models

Reference 4

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Obfuscated Activations Bypass LLM Latent-Space Defenses cites this paper.

Obfuscated Activations Bypass LLM Latent-Space Defenses Foundational Challenges in Assuring Alignment and Safety of Large Language Models

Reference 6

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Gradual Vigilance and Interval Communication: Enhancing Value Alignment in Multi-Agent Debates cites this paper.

Gradual Vigilance and Interval Communication: Enhancing Value Alignment in Multi-Agent Debates Foundational Challenges in Assuring Alignment and Safety of Large Language Models

Reference 2

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Towards Responsible Governing AI Proliferation cites this paper.

Towards Responsible Governing AI Proliferation Foundational Challenges in Assuring Alignment and Safety of Large Language Models

Reference 23

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Social Science Is Necessary for Operationalizing Socially Responsible Foundation Models cites this paper.

Social Science Is Necessary for Operationalizing Socially Responsible Foundation Models Foundational Challenges in Assuring Alignment and Safety of Large Language Models

Reference 6

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A Method for Enhancing the Safety of Large Model Generation Based on Multi-dimensional Attack and Defense cites this paper.

A Method for Enhancing the Safety of Large Model Generation Based on Multi-dimensional Attack and Defense Foundational Challenges in Assuring Alignment and Safety of Large Language Models

Reference 3

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Safeguarding Large Language Models in Real-time with Tunable Safety-Performance Trade-offs cites this paper.

Safeguarding Large Language Models in Real-time with Tunable Safety-Performance Trade-offs Foundational Challenges in Assuring Alignment and Safety of Large Language Models

Reference 3

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Mechanistic understanding and validation of large AI models with SemanticLens cites this paper.

Mechanistic understanding and validation of large AI models with SemanticLens Foundational Challenges in Assuring Alignment and Safety of Large Language Models

Reference 22

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Self-Instruct Few-Shot Jailbreaking: Decompose the Attack into Pattern and Behavior Learning cites this paper.

Self-Instruct Few-Shot Jailbreaking: Decompose the Attack into Pattern and Behavior Learning Foundational Challenges in Assuring Alignment and Safety of Large Language Models

Reference 5

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Clone-Robust AI Alignment cites this paper.

Clone-Robust AI Alignment Foundational Challenges in Assuring Alignment and Safety of Large Language Models

Reference 1

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Beyond Reward Hacking: Causal Rewards for Large Language Model Alignment cites this paper.

Beyond Reward Hacking: Causal Rewards for Large Language Model Alignment Foundational Challenges in Assuring Alignment and Safety of Large Language Models

Reference 8

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Episodic memory in AI agents poses risks that should be studied and mitigated cites this paper.

Episodic memory in AI agents poses risks that should be studied and mitigated Foundational Challenges in Assuring Alignment and Safety of Large Language Models

Reference 55

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CASE-Bench: Context-Aware SafEty Benchmark for Large Language Models cites this paper.

CASE-Bench: Context-Aware SafEty Benchmark for Large Language Models Foundational Challenges in Assuring Alignment and Safety of Large Language Models

Reference 2025

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The AI Agent Index cites this paper.

The AI Agent Index Foundational Challenges in Assuring Alignment and Safety of Large Language Models

Reference 3

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MEETING DELEGATE: Benchmarking LLMs on Attending Meetings on Our Behalf cites this paper.

MEETING DELEGATE: Benchmarking LLMs on Attending Meetings on Our Behalf Foundational Challenges in Assuring Alignment and Safety of Large Language Models

Reference 1

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JBShield: Defending Large Language Models from Jailbreak Attacks through Activated Concept Analysis and Manipulation cites this paper.

JBShield: Defending Large Language Models from Jailbreak Attacks through Activated Concept Analysis and Manipulation Foundational Challenges in Assuring Alignment and Safety of Large Language Models

Reference 6

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A Survey of Safety on Large Vision-Language Models: Attacks, Defenses and Evaluations cites this paper.

A Survey of Safety on Large Vision-Language Models: Attacks, Defenses and Evaluations Foundational Challenges in Assuring Alignment and Safety of Large Language Models

Reference 167

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Mitigating Deceptive Alignment via Self-Monitoring cites this paper.

Mitigating Deceptive Alignment via Self-Monitoring Foundational Challenges in Assuring Alignment and Safety of Large Language Models

Reference 8

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ActiveDPO: Active Direct Preference Optimization for Sample-Efficient Alignment cites this paper.

ActiveDPO: Active Direct Preference Optimization for Sample-Efficient Alignment Foundational Challenges in Assuring Alignment and Safety of Large Language Models

Reference 10

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Token-level Accept or Reject: A Micro Alignment Approach for Large Language Models cites this paper.

Token-level Accept or Reject: A Micro Alignment Approach for Large Language Models Foundational Challenges in Assuring Alignment and Safety of Large Language Models

Reference 3

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The State of Multilingual LLM Safety Research: From Measuring the Language Gap to Mitigating It cites this paper.

The State of Multilingual LLM Safety Research: From Measuring the Language Gap to Mitigating It Foundational Challenges in Assuring Alignment and Safety of Large Language Models

Reference 9

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Risks of AI-driven product development and strategies for their mitigation cites this paper.

Risks of AI-driven product development and strategies for their mitigation Foundational Challenges in Assuring Alignment and Safety of Large Language Models

Reference 4

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Linear Spatial World Models Emerge in Large Language Models cites this paper.

Linear Spatial World Models Emerge in Large Language Models Foundational Challenges in Assuring Alignment and Safety of Large Language Models

Reference 51

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AgentMisalignment: Measuring the Propensity for Misaligned Behaviour in LLM-Based Agents cites this paper.

AgentMisalignment: Measuring the Propensity for Misaligned Behaviour in LLM-Based Agents Foundational Challenges in Assuring Alignment and Safety of Large Language Models

Reference 5

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We Should Identify and Mitigate Third-Party Safety Risks in MCP-Powered Agent Systems cites this paper.

We Should Identify and Mitigate Third-Party Safety Risks in MCP-Powered Agent Systems Foundational Challenges in Assuring Alignment and Safety of Large Language Models

Reference 3

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Probing the Robustness of Large Language Models Safety to Latent Perturbations cites this paper.

Probing the Robustness of Large Language Models Safety to Latent Perturbations Foundational Challenges in Assuring Alignment and Safety of Large Language Models

Reference 3

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Agent-to-Agent Theory of Mind: Testing Interlocutor Awareness among Large Language Models cites this paper.

Agent-to-Agent Theory of Mind: Testing Interlocutor Awareness among Large Language Models Foundational Challenges in Assuring Alignment and Safety of Large Language Models

Reference 2

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Deprecating Benchmarks: Criteria and Framework cites this paper.

Deprecating Benchmarks: Criteria and Framework Foundational Challenges in Assuring Alignment and Safety of Large Language Models

Reference 4

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A Survey of Self-Evolving Agents: What, When, How, and Where to Evolve on the Path to Artificial Super Intelligence cites this paper.

A Survey of Self-Evolving Agents: What, When, How, and Where to Evolve on the Path to Artificial Super Intelligence Foundational Challenges in Assuring Alignment and Safety of Large Language Models

Reference 292

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Against racing to AGI: Cooperation, deterrence, and catastrophic risks cites this paper.

Against racing to AGI: Cooperation, deterrence, and catastrophic risks Foundational Challenges in Assuring Alignment and Safety of Large Language Models

Reference 10

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Hate in Plain Sight: On the Risks of Moderating AI-Generated Hateful Illusions cites this paper.

Hate in Plain Sight: On the Risks of Moderating AI-Generated Hateful Illusions Foundational Challenges in Assuring Alignment and Safety of Large Language Models

Reference 28

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Beyond Solving Math Quiz: Evaluating the Ability of Large Reasoning Models to Ask for Information cites this paper.

Beyond Solving Math Quiz: Evaluating the Ability of Large Reasoning Models to Ask for Information Foundational Challenges in Assuring Alignment and Safety of Large Language Models

Reference 50

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Large Language Models for Next-Generation Wireless Network Management: A Survey and Tutorial cites this paper.

Large Language Models for Next-Generation Wireless Network Management: A Survey and Tutorial Foundational Challenges in Assuring Alignment and Safety of Large Language Models

Reference 44

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Scheming Ability in LLM-to-LLM Strategic Interactions cites this paper.

Scheming Ability in LLM-to-LLM Strategic Interactions Foundational Challenges in Assuring Alignment and Safety of Large Language Models

Reference 2

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Value Drifts: Tracing Value Alignment During LLM Post-Training cites this paper.

Value Drifts: Tracing Value Alignment During LLM Post-Training Foundational Challenges in Assuring Alignment and Safety of Large Language Models

Reference 3

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Phantom Transfer: Data Poisoning can Survive Data-Level Defences cites this paper.

Phantom Transfer: Data Poisoning can Survive Data-Level Defences Foundational Challenges in Assuring Alignment and Safety of Large Language Models

Reference 2024

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Revisiting Robustness for LLM Safety Alignment via Selective Geometry Control cites this paper.

Revisiting Robustness for LLM Safety Alignment via Selective Geometry Control Foundational Challenges in Assuring Alignment and Safety of Large Language Models

Reference 1

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NEST: Nascent Encoded Steganographic Thoughts cites this paper.

NEST: Nascent Encoded Steganographic Thoughts Foundational Challenges in Assuring Alignment and Safety of Large Language Models

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BarrierSteer: LLM Safety via Learning Barrier Steering cites this paper.

BarrierSteer: LLM Safety via Learning Barrier Steering Foundational Challenges in Assuring Alignment and Safety of Large Language Models

Reference 1

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Manifold Steering Reveals the Shared Geometry of Neural Network Representation and Behavior cites this paper.

Manifold Steering Reveals the Shared Geometry of Neural Network Representation and Behavior Foundational Challenges in Assuring Alignment and Safety of Large Language Models

Reference 228

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Observation ffd801da-ca43-4ed6-b6f6-99f976febded · inbound

Belief or Circuitry? Causal Evidence for In-Context Graph Learning cites this paper.

Belief or Circuitry? Causal Evidence for In-Context Graph Learning Foundational Challenges in Assuring Alignment and Safety of Large Language Models

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-05-12T08:41:23.962333Z

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Observation 2bcdda77-c8c6-4b91-8ba4-782e7a398082 · inbound

Interpretability Can Be Actionable cites this paper.

Interpretability Can Be Actionable Foundational Challenges in Assuring Alignment and Safety of Large Language Models

Reference 82

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Observation cf4c3b87-5ed5-45d5-b964-48f9624777db · inbound

Stories in Space: In-Context Learning Trajectories in Conceptual Belief Space cites this paper.

Stories in Space: In-Context Learning Trajectories in Conceptual Belief Space Foundational Challenges in Assuring Alignment and Safety of Large Language Models

Reference 144

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Observation e4284353-edd1-4007-8b40-4521a20c3b61 · inbound

Prediction-Powered Inference Across Many Tasks for AI Evaluation & Social Science Research cites this paper.

Prediction-Powered Inference Across Many Tasks for AI Evaluation & Social Science Research Foundational Challenges in Assuring Alignment and Safety of Large Language Models

Reference 2

Resolution: metadata mismatch; arxiv_id, observed 2026-06-29T06:03:08.437075Z

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Observation b7dfc7f5-81bb-491b-ae4d-bf9f74b8ffa8 · inbound

Dissociative Identity: Language Model Agents Lack Grounding for Reputation Mechanisms cites this paper.

Dissociative Identity: Language Model Agents Lack Grounding for Reputation Mechanisms Foundational Challenges in Assuring Alignment and Safety of Large Language Models

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-06-29T00:32:53.047592Z

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Observation ca044699-010f-4031-944a-97e2aeaea091 · inbound

The Surface You Test Is Not the Surface That Breaks cites this paper.

The Surface You Test Is Not the Surface That Breaks Foundational Challenges in Assuring Alignment and Safety of Large Language Models

Reference 2

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Observation ee43106b-6bdd-435c-b545-49b57857f71f · inbound

VET: A Framework for Analyzing AI Discourse cites this paper.

VET: A Framework for Analyzing AI Discourse Foundational Challenges in Assuring Alignment and Safety of Large Language Models

Reference 166

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Observation fe12e385-1113-407c-b812-b8418590317b · inbound

Consistency Training while Mitigating Obfuscation via Rate Matching cites this paper.

Consistency Training while Mitigating Obfuscation via Rate Matching Foundational Challenges in Assuring Alignment and Safety of Large Language Models

Reference 74

Resolution: verified exact; arxiv_id, observed 2026-06-28T14:32:18.165223Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 2e78d5e7-5ce1-4849-b17c-6a011716ecbf · inbound

Black-box, Adaptive, Efficient, Transferable, Harmful, Applicable... Attacks Are All You Need to Break LLMs cites this paper.

Black-box, Adaptive, Efficient, Transferable, Harmful, Applicable... Attacks Are All You Need to Break LLMs Foundational Challenges in Assuring Alignment and Safety of Large Language Models

Reference 1

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T04:16:34.761998Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 46a39709-f2b5-41aa-892b-53ffb6583773 · inbound

A Geometric View for Understanding Concept Learning and Neuron Interpretation in Sparse Autoencoders cites this paper.

A Geometric View for Understanding Concept Learning and Neuron Interpretation in Sparse Autoencoders Foundational Challenges in Assuring Alignment and Safety of Large Language Models

Reference 38

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T16:47:09.934660Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation dcbdf9e3-9228-4c45-bb78-1a1947a62269 · inbound

Auditing Proprietary Alignment in Large Language Models: A Comparative Framework Without a Ground-Truth Standard cites this paper.

Auditing Proprietary Alignment in Large Language Models: A Comparative Framework Without a Ground-Truth Standard Foundational Challenges in Assuring Alignment and Safety of Large Language Models

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-07-02T22:17:26.017226Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 5eb8546a-7b7b-4288-9804-0fd91738197e · inbound

Distilling Safe LLM Systems via Soft Prompts for On Device Settings cites this paper.

Distilling Safe LLM Systems via Soft Prompts for On Device Settings Foundational Challenges in Assuring Alignment and Safety of Large Language Models

Reference 48

Resolution: metadata mismatch; arxiv_id, observed 2026-07-03T00:27:29.222546Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation e2cc9341-e13b-4344-aebc-f97c301d251d · inbound

Investigating The Security of Modern AI and Cloud Infrastructure cites this paper.

Investigating The Security of Modern AI and Cloud Infrastructure Foundational Challenges in Assuring Alignment and Safety of Large Language Models

Reference 12

Resolution: metadata mismatch; arxiv_id, observed 2026-07-04T08:29:42.338587Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 2811f24f-910a-4c3e-b60d-9ea0d54caf92 · inbound

Refused in Chat, Written in Code: Workflow-Level Jailbreak Construction in IDE Coding Agents cites this paper.

Refused in Chat, Written in Code: Workflow-Level Jailbreak Construction in IDE Coding Agents Foundational Challenges in Assuring Alignment and Safety of Large Language Models

Reference 10

Resolution: unresolved; no resolver link, observed 2026-07-11T22:40:37.839133Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 580bb6d7-6b73-421a-b14f-02db6794d56d · inbound

Refused in Chat, Written in Code: Workflow-Level Jailbreak Construction in IDE Coding Agents cites this paper.

Refused in Chat, Written in Code: Workflow-Level Jailbreak Construction in IDE Coding Agents Foundational Challenges in Assuring Alignment and Safety of Large Language Models

Reference 10

Resolution: unresolved; no resolver link, observed 2026-07-13T07:01:49.222325Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 078c6946-2dbb-4e66-bc77-84bc0ee45a14 · inbound

(Towards) Scalable Reliable Automated Evaluation with Large Language Models cites this paper.

(Towards) Scalable Reliable Automated Evaluation with Large Language Models Foundational Challenges in Assuring Alignment and Safety of Large Language Models

Reference 65

Resolution: unresolved; no resolver link, observed 2026-07-31T12:20:07.096313Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b30a7b2d-a07f-4801-bbb5-93ca6fd4e08b · inbound

Taxonomy-Driven Analysis of Open-Source AI Risk Mitigation Tools cites this paper.

Taxonomy-Driven Analysis of Open-Source AI Risk Mitigation Tools Foundational Challenges in Assuring Alignment and Safety of Large Language Models

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-10T04:29:11.241994Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Coverage vector

Reference resolution

Outbound references

Pith citing papers