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From the 9 of 237 papers with an AI index.

most citedCausal Panel Analysis under Parallel Trends: Lessons from a Large Reanalysis Study

23 citations

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8 papers · 1 filter

cs.LG2026

LionVote: Per-Layer Learning Rate Adaptation for Lion

Kris Atallah

Per-layer diagnostics reveal that, at the prescribed learning rate, Lion's effective scale is 2.6-2.8x too high for attention and MLP parameters and ~2x too high for normalization…

cs.LG2026

What's on My Network? Using Large Language Models to Identify Real-World IoT Devices at Scale

Rameen Mahmood, Tousif Ahmed, Sai Teja Peddinti +1

The growth of IoT devices in shared environments has outpaced our ability to identify them, posing urgent risks to privacy, safety, and accountability. This challenge is especially…

cs.LG2026

Causal Machine Learning Is Not a Panacea: A Roadmap for Observational Causal Inference in Health

Donna Tjandra, Trenton Chang, Sonali Parbhoo +8

Objective: The growing availability of large-scale observational clinical datasets and challenges in conducting randomized controlled trials have spurred enthusiasm in using causal…

cs.LG202618 cited

Humanity's Last Exam

Long Phan, Alice Gatti, Ziwen Han +1144

Benchmarks are important tools for tracking the rapid advancements in large language model (LLM) capabilities. However, benchmarks are not keeping pace in difficulty: LLMs now achi…

cs.LG2026

Large Language Models Predict Functional Outcomes after Acute Ischemic Stroke

Anjali K. Kapoor, Anton Alyakin, Jin Vivian Lee +8

Accurate prediction of functional outcomes after acute ischemic stroke can inform clinical decision-making and resource allocation. Prior work on modified Rankin Scale (mRS) predic…

cs.LG2026

Flash STU: Fast Spectral Transform Units

Y. Isabel Liu, Windsor Nguyen, Yagiz Devre +3

Recent advances in state-space model architectures have shown great promise for efficient sequence modeling, but challenges remain in balancing computational efficiency with model…