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OcuFlow Removes Eyeglass Glare in One Step and Wins 67.32% of Votes in a Blind Test
The OcuFlow authors built OcuBench, a benchmark of 11 470 images, and trained a model that removes eyeglass glare in a single step. In a blind survey it beat its…

Researchers release VR180 dataset shot on Blackmagic cameras: 1211 stereo samples
First VR180 dataset captured directly on Blackmagic URSA Cine Immersive: 636 videos, 575 photos, factory calibration, and a finding that fisheye needs 38% more…

SLVR Adds 14.2 Points on BLINK Relation to Qwen2.5-VL-7B Without Text CoT
Researchers propose SLVR: latent reasoning with typed stages. On Qwen2.5-VL-7B, the method added +9.4 on MMVP and +14.2 on BLINK Relation without generating…

Multimodal Alzheimer's AI model reaches 0.935 AUROC on 2649 patients

CARing teaches LLMs to predict diagnoses: R@30 hits 46.52% on MIMIC-IV

Visible CoT Does Not Universally Improve SQL and pandas Code Generation, New Study Finds

D-SLR Replaces Truncated SVD With Three Decompositions and No Tuning

Phase-HDC trains a model with no optimizer history and stores 16–23x less than Adam
Phase-HDC replaces Adam's moments with a threshold on the current gradient and stores 16–23x less than float32 Adam. The cost: about five points of accuracy on…

Kolmogorov-Arnold Networks Match MLP Performance With 40% Fewer Samples
In reinforcement learning, KANs reach the same results as MLPs with 40% fewer samples. Peak relative gain is up to 50%, and reward noise does not erase the…

LoopOPD Teaches Looped Language Models to Improve Through Their Own Loops

MoE Router Telemetry Leaks Fine-Tuning Data: Attack Gains 2.7–9.4 pp in Accuracy

SPERA Trained on 80,000 Hours of EEG From 29,048 People and Tested on 9 Tasks

80 Synthetic Dialogues Are Enough to Train Activation Probes for Gemma-3-27B, but Not Everywhere

Doctors Don't Ask LLMs About Diagnoses: 127 833 Queries vs. 58 Benchmarks
Analysis of 127 833 clinician queries to an AI assistant: diagnosis is only 3.7%, and a typical benchmark matches the real workload by just 31%.

FedAlphaEdit Merges Knowledge Edits from Different Organizations into One LLM Without Sharing Data
Researchers show that naively combining AlphaEdit and CollabEdit breaks down. Their FedAlphaEdit merges edits in a shared null space and comes close to centralized…









