most citedRobust Multimodal Learning via Entropy-Gated Contrastive Fusion

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stat.ML2026

RoPE attention is an exact forward-pass gradient step with softmax intact

Julie Huang, Maggie Chlon, Leon Chlon

We derive an exact gradient-step representation of the RoPE-softmax forward pass. For every deterministic RoPE-softmax attention head with arbitrary affine projection weights, we c…

stat.ML2026

Attention Deficits in Language Models: Causal Explanations for Procedural Hallucinations

Ahmed Karim, Fatima Sheaib, Zein Khamis +3

Large language models can follow complex procedures yet fail at a seemingly trivial final step: reporting a value they themselves computed moments earlier. We study this phenomenon…

stat.ML2025

Predictable Compression Failures: Order Sensitivity and Information Budgeting for Evidence-Grounded Binary Adjudication

Leon Chlon, Ahmed Karim, Maggie Chlon +1

Transformers used for evidence-grounded binary adjudication (e.g., support/refute, yes/no, or verifier-backed pass/fail decisions) can be sensitive to the order in which exchangeab…

stat.ML2025

LLMs are Bayesian, In Expectation, Not in Realization

Leon Chlon, Fatima Sheaib, Zein Khamis +3

Bayesian accounts of in-context learning face a direct objection: exact posterior predictives for exchangeable data are invariant to task-preserving order, yet transformers change…

stat.ML20251 cited

Robust Multimodal Learning via Entropy-Gated Contrastive Fusion

Leon Chlon, Maggie Chlon, MarcAntonio M. Awada

Real-world multimodal systems routinely face missing-input scenarios, and in reality, robots lose audio in a factory or a clinical record omits lab tests at inference time. Standar…