:: Library Catalog

Copertina

Salvato in:

Dettagli Bibliografici
Autori principali:	Edelman, Joe, Zhi-Xuan, Tan, Lowe, Ryan, Klingefjord, Oliver, Wang-Mascianica, Vincent, Franklin, Matija, Kearns, Ryan Othniel, Hain, Ellie, Sarkar, Atrisha, Bakker, Michiel, Barez, Fazl, Duvenaud, David, Foerster, Jakob, Gabriel, Iason, Gubbels, Joseph, Goodman, Bryce, Haupt, Andreas, Heitzig, Jobst, Jara-Ettinger, Julian, Kasirzadeh, Atoosa, Kirkpatrick, James Ravi, Koh, Andrew, Knox, W. Bradley, Koralus, Philipp, Lehman, Joel, Levine, Sydney, Marro, Samuele, Revel, Manon, Shorin, Toby, Sutherland, Morgan, Tessler, Michael Henry, Vendrov, Ivan, Wilken-Smith, James
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Machine Learning
Accesso online:	https://arxiv.org/abs/2512.03399
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Theory-Grounded Evaluation of Human-Like Fallacy Patterns in LLM Reasoning
di: Richardson, Andrew Keenan, et al.
Pubblicazione: (2025)

Characterizing AI Agents for Alignment and Governance
di: Kasirzadeh, Atoosa, et al.
Pubblicazione: (2025)

Quantifying construct validity in large language model evaluations
di: Kearns, Ryan Othniel
Pubblicazione: (2026)

Measurement challenges in AI catastrophic risk governance and safety frameworks
di: Kasirzadeh, Atoosa
Pubblicazione: (2024)

Two Types of AI Existential Risk: Decisive and Accumulative
di: Kasirzadeh, Atoosa
Pubblicazione: (2024)

Model-Based Soft Maximization of Suitable Metrics of Long-Term Human Power
di: Heitzig, Jobst, et al.
Pubblicazione: (2025)

AI Safety for Everyone
di: Gyevnar, Balint, et al.
Pubblicazione: (2025)

Beyond Model Interpretability: Socio-Structural Explanations in Machine Learning
di: Smart, Andrew, et al.
Pubblicazione: (2024)

Explanation Hacking: The perils of algorithmic recourse
di: Sullivan, Emily, et al.
Pubblicazione: (2024)

Bridging the Gap in the Responsible AI Divides
di: Gyevnár, Bálint, et al.
Pubblicazione: (2026)

SafetyNet: Detecting Harmful Outputs in LLMs by Modeling and Monitoring Deceptive Behaviors
di: Chaudhary, Maheep, et al.
Pubblicazione: (2025)

Understanding Addition in Transformers
di: Quirke, Philip, et al.
Pubblicazione: (2023)

Same Question, Different Words: A Latent Adversarial Framework for Prompt Robustness
di: Fu, Tingchen, et al.
Pubblicazione: (2025)

What are human values, and how do we align AI to them?
di: Klingefjord, Oliver, et al.
Pubblicazione: (2024)

Deterministic Model of Incremental Multi-Agent Boltzmann Q-Learning: Transient Cooperation, Metastability, and Oscillations
di: Goll, David, et al.
Pubblicazione: (2024)

The River Method
di: Döring, Michelle, et al.
Pubblicazione: (2025)

Capital Inequality Induced Business Cycles
di: Nagel, Sören, et al.
Pubblicazione: (2023)

Query Circuits: Explaining How Language Models Answer User Prompts
di: Wu, Tung-Yu, et al.
Pubblicazione: (2025)

Epistemic Injustice in Generative AI
di: Kay, Jackie, et al.
Pubblicazione: (2024)

AI, Digital Platforms, and the New Systemic Risk
di: Hacker, Philipp, et al.
Pubblicazione: (2025)

Rethinking AI Cultural Alignment
di: Bravansky, Michal, et al.
Pubblicazione: (2025)

Towards Interpretable Sequence Continuation: Analyzing Shared Circuits in Large Language Models
di: Lan, Michael, et al.
Pubblicazione: (2023)

Understanding Addition and Subtraction in Transformers
di: Quirke, Philip, et al.
Pubblicazione: (2024)

The More You Automate, the Less You See: Hidden Pitfalls of AI Scientist Systems
di: Luo, Ziming, et al.
Pubblicazione: (2025)

Non-maximizing policies that fulfill multi-criterion aspirations in expectation
di: Dima, Simon, et al.
Pubblicazione: (2024)

Beyond Linear Probes: Dynamic Safety Monitoring for Language Models
di: Oldfield, James, et al.
Pubblicazione: (2025)

The Philosophic Turn for AI Agents: Replacing centralized digital rhetoric with decentralized truth-seeking
di: Koralus, Philipp
Pubblicazione: (2025)

Token Taxes: mitigating AGI's economic risks
di: Irwin, Lucas, et al.
Pubblicazione: (2026)

Large Language Models Relearn Removed Concepts
di: Lo, Michelle, et al.
Pubblicazione: (2024)

VAL-Bench: Belief Consistency as a measure for Value Alignment in Language Models
di: Gupta, Aman, et al.
Pubblicazione: (2025)

Interpreting Context Look-ups in Transformers: Investigating Attention-MLP Interactions
di: Neo, Clement, et al.
Pubblicazione: (2024)

A dynamic network model of societal complexity and resilience inspired by Tainter's theory of collapse
di: Schunck, Florian, et al.
Pubblicazione: (2021)

Enhancing Neural Network Interpretability with Feature-Aligned Sparse Autoencoders
di: Marks, Luke, et al.
Pubblicazione: (2024)

Do Sparse Autoencoders Generalize? A Case Study of Answerability
di: Heindrich, Lovis, et al.
Pubblicazione: (2025)

Towards Understanding Subliminal Learning: When and How Hidden Biases Transfer
di: Schrodi, Simon, et al.
Pubblicazione: (2025)

Visualizing Neural Network Imagination
di: Wichers, Nevan, et al.
Pubblicazione: (2024)

Learning Interpretable Collective Variables for Spreading Processes on Networks
di: Lücke, Marvin, et al.
Pubblicazione: (2023)

Recurrence threshold selection for obtaining robust recurrence characteristics in different embedding dimensions
di: Kraemer, K. Hauke, et al.
Pubblicazione: (2025)

Large population limits of Markov processes on random networks
di: Lücke, Marvin, et al.
Pubblicazione: (2022)

LLMs Don't Know Their Own Decision Boundaries: The Unreliability of Self-Generated Counterfactual Explanations
di: Mayne, Harry, et al.
Pubblicazione: (2025)