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Understand new AI research with readable explanations and links to the original papers.
Governing What You Cannot Observe: Adaptive Runtime Governance for Autonomous AI Agents Autonomous AI agents are increasingly common in production, but they...
Assessing Y-Axis Influence: Bias in Multimodal Language Models on Chart-to-Table Translation Multimodal Language Models (MLMs) are increasingly used to conve...
The Price of Agreement: Measuring LLM Sycophancy in Agentic Financial Applications This research explores the risks of "sycophancy" in artificial intelligenc...
Interoceptive machine framework: Toward interoception-inspired regulatory architectures in artificial intelligence This paper introduces the "interoceptive m...
Learning to Rotate: Temporal and Semantic Rotary Encoding for Sequential Modeling This paper proposes a new way to think about how Transformer models underst...
Hierarchical Behaviour Spaces (HBS) is a new approach to reinforcement learning designed to help agents navigate environments that require reasoning over ver...
Sparse Personalized Text Generation with Multi-Trajectory Reasoning Large Language Models (LLMs) are increasingly used to provide personalized experiences, b...
Toward a Science of Intent: Closure Gaps and Delegation Envelopes for Open-World AI Agents This paper addresses a fundamental challenge in AI deployment: why...
S-SONDO: Self-Supervised Knowledge Distillation for General Audio Foundation Models General audio foundation models have become incredibly powerful, but they...
STELLAR-E: a Synthetic, Tailored, End-to-end LLM Application Rigorous Evaluator As Large Language Models (LLMs) become central to industries like finance and...
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