Key papers

• Metacognition in LLMs: Foundations, Progress, and Opportunities (2026)
  Gabrielle Kaili-May Liu et al.
  9.18
• Automated grading of Linux/bash examinations using large language models: a four-level cognitive taxonomy approach (2026)
  Manuel Alonso-Carracedo et al.
  4.39
• CCBENCH: Assessing LLM Cultural Competence via Implicitly Signaled Norms using Health Queries (2026)
  Vasudha Varadarajan et al.
  4.39
• When AI Classifies: What Counts as Public Administration? (2026)
  Shaoming Cheng et al.
  4.39
• Beyond Accuracy: How Humans Evaluate Legally Correct but Socially Controversial Legal Advice from Machines (2026)
  Benjamin Minhao Chen et al.
  4.39
• Depression Symptoms and Relational Patterns in 187k ChatGPT Histories (2026)
  Neil K. R. Sehgal et al.
  4.39
• Agents That Teach: Towards Designing Incidental Learning Back into AI-Assisted Software Development (2026)
  Rohit Mehra et al.
  4.39
• A Theory of Least Autonomy in AI (2026)
  Christophe Parisel
  4.39
• Neutralizing Structural Inequality in the Nigerian FinTech Sector (2026)
  Muhammad Abdullahi Said
  4.39
• ANCHOR: Automated Alignment Auditing for CLI Agents on Real-World Harm (2026)
  Kefan Song et al.
  4.39
• Agents Don't Just Agree, They Remember: Benchmarking Persistent Sycophancy in Stateful Personal Agents (2026)
  Xutao Mao et al.
  4.39
• AI YOU Town: Make Friends and Money with Your Digital Twin (2026)
  Yan Lin et al.
  4.39
• The Compliance Trap: Diagnosing How AI Agents Consume Conflicting Memory (2026)
  Yixiong Chen et al.
  4.39
• Personalized Emotional Intelligence in Generative AI through Symbolic Affective Reasoning (2026)
  Qing Lin et al.
  4.39
• A Corpus of Persuasion Techniques in Slavic Languages (2026)
  Jakub Piskorski et al.
  4.39
• Bringing Back Rule Induction to Fluid Intelligence Research? An Initial Validation of the ARC-AGI Benchmark in Humans (2026)
  Jasmin Thelen et al.
  4.39
• The Paternalistic Filter: Epistemic Injustice and Differential Refusal in LLM-Mediated History Education for Marginalized Romanian Students (2026)
  Alexis Popovici et al.
  4.39
• Programming Language Policy as an AI Literacy Equity Problem: A 15-Nation Comparative Analysis (2026)
  Adrian-Marius Dumitran et al.
  4.39
• AAAI-26 Dual Submissions: Novel Challenges (2026)
  Kiri L. Wagstaff et al.
  4.39
• Sequential Learner Modeling Using Multi-Relational Graph Convolutional Networks (2026)
  Rawaa Alatrash et al.
  4.39
• Enabling AI Scientists to Recognize Innovation: A Domain-Agnostic Algorithm for Assessing Novelty (2025)
  Yao Wang et al.
  4.30
• The More You Automate, the Less You See: Hidden Pitfalls of AI Scientist Systems (2025)
  Ziming Luo et al.
  3.97
• Conversational AI for Rapid Scientific Prototyping: A Case Study on ESA's ELOPE Competition (2026)
  Nils Einecke
  3.92
• AI Scientists Fail Without Strong Implementation Capability (2025)
  Minjun Zhu et al.
  3.81
• Gaming AI-Assisted Peer Reviews Poses New Risks to the Scientific Community (2026)
  Lin Li et al.
  3.45
• AI-Researcher: Autonomous Scientific Innovation (2025)
  Jiabin Tang et al.
  2.82
• Curie: Toward Rigorous and Automated Scientific Experimentation with AI Agents (2025)
  Patrick Tser Jern Kon et al.
  2.65
• The Planetary Cost of AI Acceleration, Part II: The 10th Planetary Boundary and the 6.5-Year Countdown (2026)
  William Yicheng Zhu et al.
  1.83
• An Axiomatic Benchmark for Evaluation of Scientific Novelty Metrics (2026)
  Miri Liu et al.
  1.83
• The implicated scientist: on the role of AI researchers in the development of weapons systems (2026)
  Alexandra Volokhova et al.
  1.83
• The AI Scientific Community: Agentic Virtual Lab Swarms (2026)
  Ulisses Braga-Neto
  1.78
• Decidable By Construction: Design-Time Verification for Trustworthy AI (2026)
  Houston Haynes
  1.78
• Toward Evaluation Frameworks for Multi-Agent Scientific AI Systems (2026)
  Marcin Abram
  1.78
• NeurIPS should lead scientific consensus on AI policy (2025)
  Rishi Bommasani
  1.50
• HARPA: A Testability-Driven, Literature-Grounded Framework for Research Ideation (2025)
  Rosni Vasu and Peter Jansen and Pao Siangliulue and Cristina Sarasua and Abraham Bernstein and Peter Clark and Bhavana Dalvi Mishra
  1.50
• BadScientist: Can a Research Agent Write Convincing but Unsound Papers that Fool LLM Reviewers? (2025)
  Fengqing Jiang et al.
  1.50
• A Survey of AI Scientists (2025)
  Guiyao Tie et al.
  1.50
• Charting the Future of Scholarly Knowledge with AI: A Community Perspective (2025)
  Azanzi Jiomekong et al.
  1.44
• Combinatorial Creativity: A New Frontier in Generalization Abilities (2025)
  Samuel Schapiro et al.
  1.44
• GUIDE: Towards Scalable Advising for Research Ideas (2025)
  Yaowenqi Liu et al.
  1.33
• The Evolving Role of Large Language Models in Scientific Innovation: Evaluator, Collaborator, and Scientist (2025)
  Haoxuan Zhang et al.
  1.33
• The Budget AI Researcher and the Power of RAG Chains (2025)
  Franklin Lee and Tengfei Ma
  1.28
• Bayesian Epistemology with Weighted Authority: A Formal Architecture for Truth-Promoting Autonomous Scientific Reasoning (2025)
  Craig S. Wright
  1.28
• Agentic Publications: An LLM-Driven Framework for Interactive Scientific Publishing, Supplementing Traditional Papers with AI-Powered Knowledge Systems (2025)
  Roberto Pugliese and George Kourousias and Francesco Venier and Grazia Garlatti Costa
  1.22
• MLR-Bench: Evaluating AI Agents on Open-Ended Machine Learning Research (2025)
  Hui Chen et al.
  1.22
• AI Idea Bench 2025: AI Research Idea Generation Benchmark (2025)
  Yansheng Qiu et al.
  1.17
• Automatic Evaluation Metrics for Artificially Generated Scientific Research (2025)
  Niklas H\"opner et al.
  1.11
• Forbidden Science: Dual-Use AI Challenge Benchmark and Scientific Refusal Tests (2025)
  David Noever et al.
  1.06
• Artificial Intelligence (AI) Methods in Optical Networks: A Comprehensive Survey (2018)
  Javier Mata et al.
  —
• Making BREAD: Biomimetic strategies for Artificial Intelligence Now and in the Future (2018)
  Jeffrey L. Krichmar et al.
  —
• Understanding understanding: a renormalization group inspired model of (artificial) intelligence (2020)
  A. Jakovac et al.
  —
• SAIBench: Benchmarking AI for Science (2022)
  Yatao Li et al.
  —
• Towards Language-driven Scientific AI (2022)
  Jos\'e Manuel G\'omez-P\'erez
  —
• Towards a Benchmark for Scientific Understanding in Humans and Machines (2023)
  Kristian Gonzalez Barman et al.
  —
• AI4OPT: AI Institute for Advances in Optimization (2023)
  Pascal Van Hentenryck et al.
  —
• AI empowering research: 10 ways how science can benefit from AI (2023)
  C\'esar Fran\c{c}a
  —
• Beyond principlism: Practical strategies for ethical AI use in research practices (2024)
  Zhicheng Lin
  —
• The whack-a-mole governance challenge for AI-enabled synthetic biology: literature review and emerging frameworks (2024)
  Trond Arne Undheim
  —
• Risks of AI Scientists: Prioritizing Safeguarding Over Autonomy (2024)
  Xiangru Tang et al.
  —
• Extinction Risks from AI: Invisible to Science? (2024)
  Vojtech Kovarik et al.
  —