arXiv:2601.12193v1 Announce Type: new Abstract: Modern video retrieval systems are expected to handle diverse tasks ranging from corpus-level retrieval and fine-grained moment localization to flexible multimodal querying. Specialized architectures achieve strong retrieval performance by training modality-specific encoders on massive datasets, but they lack the ability to process composed multimodal queries. In contrast, multimodal LLM (MLLM)-based methods support rich multimodal search but their retrieval performance remains well below that of specialized systems. We present VIRTUE, an MLLM-based versatile video […]

Ver mais

arXiv:2603.12343v1 Announce Type: new Abstract: Treatment-resistant depression (TRD) is a severe form of major depressive disorder in which patients do not achieve remission despite multiple adequate treatment trials. Evidence across pharmacologic options for TRD remains limited, and trials often do not fully capture patient-reported tolerability. Large-scale online peer-support narratives therefore offer a complementary lens on how patients describe and evaluate medications in real-world use. In this study, we curated a corpus of 5,059 Reddit posts explicitly referencing TRD […]

Ver mais

Tool: Merge State Visualizer Bram Cohen wrote about his coherent vision for the future of version control using CRDTs, illustrated by 470 lines of Python. I fed that Python (minus comments) into Claude and asked for an explanation, then had it use Pyodide to build me an interactive UI for seeing how the algorithms work. Tags: vcs, pyodide, bram-cohen, crdt

Ver mais

arXiv:2602.21509v1 Announce Type: new Abstract: The goal of fair clustering is to find clusters such that the proportion of sensitive attributes (e.g., gender, race, etc.) in each cluster is similar to that of the entire dataset. Various fair clustering algorithms have been proposed that modify standard K-means clustering to satisfy a given fairness constraint. A critical limitation of several existing fair clustering algorithms is that the number of parameters to be learned is proportional to the sample size […]

Ver mais

Simulation theory has been thrown around the internet for years, stemming from the early days of computing. It has long been theorized that everything around us is the result of a computer generated simulation, a fake reality that is being fed through us and presented as real. The Matrix is the first popular reference of simulation theory, and made the idea not only more understood by the general public but more accepted as well. Technology Acceleration Moore’s Law […]

Ver mais

We study the problem of learning Transformer-based sequence models with black-box access to their outputs. In this setting, a learner may adaptively query the oracle with any sequence of vectors and observe the corresponding real-valued output. We begin with the simplest case, a single-head softmax-attention regressor. We show that for a model with width $d$, there is an elementary algorithm to learn the parameters of single-head attention exactly with $O(d^2)$ queries. Further, we show that if there exists […]

Ver mais