arXiv:2601.20046v1 Announce Type: new Abstract: Metastatic castration-resistant prostate cancer (mCRPC) is a highly aggressive disease with poor prognosis and heterogeneous treatment response. In this work, we developed and externally validated a visit-level 180-day mortality risk model using longitudinal data from two Phase III cohorts (n=526 and n=640). Only visits with observable 180-day outcomes were labeled; right-censored cases were excluded from analysis. We compared five candidate architectures: Long Short-Term Memory, Gated Recurrent Unit (GRU), Cox Proportional Hazards, Random Survival […]

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arXiv:2603.09985v1 Announce Type: new Abstract: Large language models (LLMs) have demonstrated remarkable capabilities across diverse tasks, yet their ability to accurately assess their own confidence remains poorly understood. We present an empirical study investigating whether LLMs exhibit patterns reminiscent of the Dunning-Kruger effect — a cognitive bias where individuals with limited competence tend to overestimate their abilities. We evaluate four state-of-the-art models (Claude Haiku 4.5, Gemini 2.5 Pro, Gemini 2.5 Flash, and Kimi K2) across four benchmark datasets […]

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Here’s something I’ve wondered about before: are there good mnemonics for chemical element symbols? Some element symbols are based on Latin or German names and seem arbitrary to English speakers, such as K (kalium) for potassium or Fe (ferrum) for iron. However, these elements are very common and so their names and symbols are familiar. When you take out the elements whose symbols are mnemonic in another language, every element symbol begins with the first letter of the […]

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Why depth yields a genuine computational advantage over shallow methods remains a central open question in learning theory. We study this question in a controlled high-dimensional Gaussian setting, focusing on compositional target functions. We analyze their learnability using an explicit three-layer fitting model trained via layer-wise spectral estimators. Although the target is globally a high-degree polynomial, its compositional structure allows learning to proceed in stages: an intermediate representation reveals structure that is inaccessible at the input level. This […]

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Automated Speciation (Bifurcation) When the Regulator returns UNSAT (identifying that performance and diversity constraints are mutually exclusive), the system triggers a Bifurcation Event. This partitions the population into specialized sub-cradles, proved by Lean 4 to be Pareto-optimal transitions. JAX-Native Parallelism Implementation utilizes JAX collective operations for O(1) scaling across multi-GPU/TPU nodes. The Symbolic Tier (Z3/Lean) runs asynchronously on CPU nodes, maintaining high-throughput JaxMARL environment rollouts. submitted by /u/Regular_Run3923 [link] [comments]

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arXiv:2601.18921v1 Announce Type: new Abstract: The integration of large-scale chemical databases represents a critical bottleneck in modern cheminformatics research, particularly for machine learning applications requiring high-quality, multi-source validated datasets. This paper presents a case study of integrating three major public chemical repositories: PubChem (176 million compounds), ChEMBL, and eMolecules, to construct a curated dataset for molecular property prediction. We investigate whether byte-offset indexing can practically overcome brute-force scalability limits while preserving data integrity at hundred-million scale. Our results […]

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arXiv:2602.21337v1 Announce Type: new Abstract: AI is becoming increasingly integrated into everyday life, both in professional work environments and in leisure and entertainment contexts. This integration requires AI to move beyond acting as an assistant for informational or transactional tasks toward a genuine collaborative partner. Effective collaboration, whether between humans or between humans and AI, depends on establishing and maintaining common ground: shared beliefs, assumptions, goals, and situational awareness that enable coordinated action and efficient repair of misunderstandings. […]

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arXiv:2602.18550v1 Announce Type: new Abstract: Resume screening is perceived as a particularly suitable task for LLMs given their ability to analyze natural language; thus many entities rely on general purpose LLMs without further adapting them to the task. While researchers have shown that some LLMs are biased in their selection rates of different demographics, studies measuring the validity of LLM decisions are limited. One of the difficulties in externally measuring validity stems from lack of access to a […]

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arXiv:2601.12220v1 Announce Type: new Abstract: We present an algorithm for normalizing emph{Batched Einstein Summation} expressions by mapping mathematically equivalent formulations to a unique normal form. Batches of einsums with the same Einstein notation that exhibit substantial data reuse appear frequently in finite element methods (FEM), numerical linear algebra, and computational chemistry. To effectively exploit this temporal locality for high performance, we consider groups of einsums in batched form. Representations of equivalent batched einsums may differ due to index […]

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My ML research notes are continuously updated to cover both theory and implementation. I chose this format because writing a book for Machine Learning no longer makes sense; a dynamic, evolving resource is the only way to keep up with the industry. Check it out here: https://github.com/roboticcam/machine-learning-notes submitted by /u/Delicious_Screen_789 [link] [comments]

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