The Selection
No mentions found
This entity hasn't been tracked yet, or Iris is still building its knowledge base.
Related Articles from SNS
Correcting for Global Synonymous Selection Improves the Accuracy of Episodic Positive Selection Inference
The ratio of nonsynonymous to synonymous substitution rates ({omega}) constitutes a fundamental parameter for inferring adaptive protein evolution, predicated upon the assumption that synonymous substitutions are selectively inert. This premise, however, is increasingly untenable given evidence of selection acting on synonymous substitutions, driven by various biological processes such as translational efficiency and mRNA stability. In this study, we demonstrate that unmodelled synonymous...
PRISM: Self-Pruning Intrinsic Selection Method for Training-Free Multimodal Data Selection
arXiv:2502.12119v4 Announce Type: replace Abstract: Visual instruction tuning adapts pre-trained Multimodal Large Language Models (MLLMs) to follow human instructions for real-world applications. However, the rapid growth of these datasets introduces significant redundancy, leading to increased computational costs. Existing methods for selecting instruction data aim to prune this redundancy, but predominantly rely on computationally demanding techniques such as proxy-based inference or...
Causal Modeling of Selection in Evolution
Announce Type: new Abstract: Understanding potential selection in data is crucial for causal discovery; we argue that "selection" in common narratives takes two forms, which we term static and evolutionary selection, respectively. Static selection refers to a one-shot filtering process where observed data consist of a subset of the population of interest, as in survey volunteer bias. Evolutionary selection, in contrast, operates through repeated rounds of differential fitness in...
MAOAM: Unified Object and Material Selection with Vision-Language Models
arXiv:2606.04880v1 Announce Type: new Abstract: Selection is a core operation in interactive image editing. To be practical, a user should be able to specify and disambiguate the desired selection region through either text or click-based interactions, and the system should support selecting not only objects but also other criteria, such as materials. Material-based selection is valuable for tasks like re-texturing surfaces or editing instances of a specific material.
Singapore Airlines limits Business Class advance seat selection based on fare type and membership
Singapore Airlines limits Business Class advance seat selection based on fare type and membership For seat selections made on or after Jun 2, passengers booked on Business Lite fares, as well as Saver, Advantage or Promo awards, are limited to a smaller pool of Business Class seats when making advance seat selections. Singapore Airlines (SIA) has introduced new changes to its advance Business Class seat selection policy, limiting access to preferred seats for passengers travelling on...
Unifying and Optimizing Data Values for Selection via Sequential Decision-Making
arXiv:2502.04554v2 Announce Type: replace Abstract: Data selection has emerged as a crucial downstream application of data valuation, yet the theoretical foundations for using data values in selection remain underexplored. We reformulate data selection as a sequential decision-making problem where the optimal selection sequence arises from dynamic programming, and data values can be understood as encodings of this optimal sequence. This framework unifies and reinterprets existing methods...
More than 250 athletes provisionally selected to represent Singapore at 2026 Asian Games
More than 250 athletes provisionally selected to represent Singapore at 2026 Asian Games Defending Asian Games champions Shanti Pereira and Ryan Lo are among those selected, along with Loh Kean Yew and the Quah siblings. SINGAPORE: A total of 256 athletes across 23 sports have been provisionally selected to represent Singapore at the upcoming Asian Games in Japan. In a media release issued on Tuesday (Jun 2), the Singapore National Olympic Council (SNOC) announced the first batch of athletes...
BLISS: A Lightweight Bilevel Influence Scoring Method for Data Selection in Language Model Pretraining
Announce Type: replace Abstract: Effective data selection is essential for pretraining large language models (LLMs), enhancing efficiency and improving generalization to downstream tasks. However, existing approaches often require leveraging external pretrained models, making it difficult to disentangle the effects of data selection from those of the external pretrained models. In addition, they often overlook the long-term impact of selected data if the model is trained to convergence,...
LARK: Learnability-Grounded Trajectory Selection for Efficient Reasoning Distillation
Announce Type: new Abstract: We study trajectory selection for reasoning distillation, where teacher-generated reasoning trajectories are selectively used as supervision for a student model. Existing methods rely on heuristics such as trajectory quality or model confidence, but they often overlook whether a trajectory is learnable by the student. In this paper, we present LARK, a learnability-grounded method for reasoning trajectory selection.
Once-For-All: A Train-Once and Select-Anytime Framework for Multimodal Instruction Tuning
arXiv:2605.26761v2 Announce Type: replace Abstract: Multimodal instruction tuning is the de facto recipe for adapting vision language models (VLMs), yet instruction data are highly redundant, making data selection critical for training efficiency. Existing methods derive selection signals from a specific model or dataset, so whenever the target model or candidate pool changes, the criteria must be recomputed from scratch at substantial cost. To address this, we propose OFA, a data selection...