SnapKV: LLM Knows What You are Looking for Before Generation
View PDF
Test Information Space
Instructors as Innovators: a Future-focused Approach to New AI Learning Opportunities, With Prompts
FlashSpeech: Efficient Zero-Shot Speech Synthesis
OpenELM: An Efficient Language Model Family with Open-source Training and Inference Framework
Multi-Head Mixture-of-Experts
View PDF
The Instruction Hierarchy: Training LLMs to Prioritize Privileged Instructions
Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone
View PDF
Design of highly functional genome editors by modeling the universe of CRISPR-Cas sequences
Download PDF
LLM Agents can Autonomously Exploit One-day Vulnerabilities
The ethics of advanced ai assistants 2024 i
AI Index Report 2024 – Artificial Intelligence Index
Is artificial intelligence the great filter that makes advanced technical civilisations rare in the universe?
(Conversely, substrates are like Fermi. Where are they found?)
Leave No Context Behind: Efficient Infinite Context Transformers with Infini-attention
OpenEQA: From word models to world models
OpenEQA combines challenging open-vocabulary questions with the ability to answer in natural language. This results in a straightforward benchmark that demonstrates a strong understanding of the environment—and poses a considerable challenge to current foundational models. We hope this work motivates additional research into helping AI understand and communicate about the world it sees.
(PDF) Ethics of Quantum Technologies: A Scoping Review
The majority of the research has focused on the potential impact of quantum technologies on privacy and security, the potential impact of quantum technologies on the trust of those systems, and the potential for creating new forms of inequality in access to the technology.
Anil, C., Durmus, E., Sharma, M., Benton, J., Kundu, S., Batson, J., ... & Duvenaud, D. (2024). Many-shot Jailbreaking.
Long contexts represent a new front in the struggle to control LLMs. We explored a family of attacks that are newly feasible due to longer context lengths, as well as candidate mitigations. We found that the effectiveness of attacks, and of in-context learning more generally, could be characterized by simple power laws. This provides a richer source of feedback for mitigating long-context attacks than the standard approach of measuring frequency of success
Does Transformer Interpretability Transfer to RNNs?
Codegemma report
ReALM: Reference Resolution As Language Modeling
Jamba: A Hybrid Transformer-Mamba Language Model
Nay, J. J., Karamardian, D., Lawsky, S. B., Tao, W., Bhat, M., Jain, R., ... & Kasai, J. (2024). Large language models as tax attorneys: a case study in legal capabilities emergence. Philosophical Transactions of the Royal Society A, 382(2270), 20230159.
Navigating the future of work perspectives on automation ai and economic prosperity
Long-form factuality in large language models
FACT SHEET: Vice President Harris Announces OMB Policy to Advance Governance, Innovation, and Risk Management in Federal Agencies’ Use of Artificial Intelligence | The White House
OMB’s first government-wide policy
Cultural Bias in Explainable AI Research: A Systematic Analysis | Journal of Artificial Intelligence Research
The role of computational science in digital twins
Language Models Can Reduce Asymmetry in Information Markets
Avery, J. J., Abril, P. S., & del Riego, A. ChatGPT, Esq.: Recasting Unauthorized Practice of Law in the Era of Generative AI. Yale Journal of Law & Technology, 26(1).
Standardized nomenclature for litigational legal prompting in generative language models
Scientific Educations Among U.S. Judges