Large Language Models Generate Harmful Content Using a Distinct, Unified Mechanism

Large Language Models Generate Harmful Content Using a Distinct, Unified Mechanism | ScienceToStartup

Freshness

Paper proof surface

Canonical route: /paper/large-language-models-generate-harmful-content-using-a-distinct-unified-mechanism

building

Observed: 2026-04-13
Fresh until: 2026-04-27
Coverage: 50%
Source count: 3
Stale after: 2026-04-27

Proof data is outside the preferred freshness window.

Proof Quality

One canonical proof ledger now drives the badge, counts, indexing, and commercialization gating.

Verification pending

Last verified: 2026-04-13
References: 0
Sources: 3
Coverage: 50%

Commercialization rails stay hidden until proof clears: proof_status, references_count.

Search indexing stays off until proof clears: proof_status, references_count.

Agent Handoff

Large Language Models Generate Harmful Content Using a Distinct, Unified Mechanism

Canonical ID large-language-models-generate-harmful-content-using-a-distinct-unified-mechanism | Route /paper/large-language-models-generate-harmful-content-using-a-distinct-unified-mechanism

REST example

curl https://sciencetostartup.com/api/v1/agent-handoff/paper/large-language-models-generate-harmful-content-using-a-distinct-unified-mechanism

MCP example

{
  "tool": "get_paper",
  "arguments": {
    "arxiv_id": "2604.09544"
  }
}

source_context

{
  "surface": "paper",
  "mode": "paper",
  "query": "Large Language Models Generate Harmful Content Using a Distinct, Unified Mechanism",
  "normalized_query": "2604.09544",
  "route": "/paper/large-language-models-generate-harmful-content-using-a-distinct-unified-mechanism",
  "paper_ref": "large-language-models-generate-harmful-content-using-a-distinct-unified-mechanism",
  "topic_slug": null,
  "benchmark_ref": null,
  "dataset_ref": null
}

PDF Viewer

100%

Open Full PDF

References (55)

[1]

LLMs Encode Harmfulness and Refusal Separately

2025Jiachen Zhao, Jing Huang et al.

[2]

Persona Features Control Emergent Misalignment

2025Miles Wang, Tom Dupré la Tour et al.

[3]

Model Organisms for Emergent Misalignment

2025Edward Turner, Anna Soligo et al.

[4]

AI-induced sexual harassment: Investigating Contextual Characteristics and User Reactions of Sexual Harassment by a Companion Chatbot

2025M. Namvarpour, Harrison Pauwels et al.

[5]

Command A: An Enterprise-Ready Large Language Model

2025Team Cohere, Aakanksha et al.

[6]

Training large language models on narrow tasks can lead to broad misalignment

2025Jan Betley, Daniel Tan et al.

[7]

Position-aware Automatic Circuit Discovery

2025Tal Haklay, Hadas Orgad et al.

[8]

Deliberative Alignment: Reasoning Enables Safer Language Models

2024Melody Y. Guan, Manas R. Joglekar et al.

[9]

On Evaluating the Durability of Safeguards for Open-Weight LLMs

2024Xiangyu Qi, Boyi Wei et al.

[10]

Booster: Tackling Harmful Fine-tuning for Large Language Models via Attenuating Harmful Perturbation

2024Tiansheng Huang, Sihao Hu et al.

[11]

Revisiting the Robust Alignment of Circuit Breakers

2024Leo Schwinn, Simon Geisler

[12]

Refusal in Language Models Is Mediated by a Single Direction

2024Andy Arditi, Oscar Obeso et al.

[13]

Safety Alignment Should Be Made More Than Just a Few Tokens Deep

2024Xiangyu Qi, Ashwinee Panda et al.

[14]

Improving Alignment and Robustness with Circuit Breakers

2024Andy Zou, Long Phan et al.

[15]

Language is primarily a tool for communication rather than thought

2024E. Fedorenko, Steven T Piantadosi et al.

[16]

Defending Large Language Models Against Jailbreak Attacks via Layer-specific Editing

2024Wei Zhao, Zhe Li et al.

[17]

Jailbreaking Leading Safety-Aligned LLMs with Simple Adaptive Attacks

2024Maksym Andriushchenko, Francesco Croce et al.

[18]

Dissecting Language Models: Machine Unlearning via Selective Pruning

2024Nicholas Pochinkov, Nandi Schoots

[19]

Defending LLMs against Jailbreaking Attacks via Backtranslation

2024Yihan Wang, Zhouxing Shi et al.

[20]

A StrongREJECT for Empty Jailbreaks

2024Alexandra Souly, Qingyuan Lu et al.

Showing 20 of 55 references

Large Language Models Generate Harmful Content Using a Distinct, Unified Mechanism

Use the canonical paper page as a proof artifact

Paper proof surface

Large Language Models Generate Harmful Content Using a Distinct, Unified Mechanism

Research neighborhood

Claim map

Competitive landscape

Subscribe to the weekly brief

References (55)

Related Resources

Large Language Models Generate Harmful Content Using a Distinct, Unified Mechanism

Use the canonical paper page as a proof artifact

Paper proof surface

Large Language Models Generate Harmful Content Using a Distinct, Unified Mechanism

Research neighborhood

Claim map

Competitive landscape

Subscribe to the weekly brief

References (55)

Related Papers

Related Resources