Latest AI/ML News
9894 articles · arXiv cs.LG
arXiv:2609.39437v1 Announce Type: new Abstract: Large language models (LLMs) encode substantial latent geographic knowledge, yet they reason poorly ov…
arXiv:2609.39436v1 Announce Type: new Abstract: Reinforcement learning with a verifiable reward (RLVR) offers a scalable approach to training language…
arXiv:2609.39408v1 Announce Type: new Abstract: Population loss can remain nearly constant while a neural network learns a substantially more predicti…
arXiv:2609.39405v1 Announce Type: new Abstract: Task vectors provide a simple mechanism for composing learned capabilities through model merging. Howe…
arXiv:2609.39390v1 Announce Type: new Abstract: Few-Shot Class-Incremental Learning (FSCIL) addresses the challenge of learning new classes from very…
arXiv:2609.39387v1 Announce Type: new Abstract: Neural operators increasingly benefit from pretraining on numerical simulations, yet adapting them for…
arXiv:2609.39386v1 Announce Type: new Abstract: Pretrained time-series foundation models (TSFMs) are evaluated as forecasters of future values, yet fo…
arXiv:2609.39383v1 Announce Type: new Abstract: Large language model (LLM)-based automatic heuristic design (AHD) iteratively proposes and refines heu…
arXiv:2609.39374v1 Announce Type: new Abstract: Synthetic time series are increasingly used for data augmentation, privacy-preserving data sharing, an…
arXiv:2609.39361v1 Announce Type: new Abstract: While most attention logits can be computed in low precision without degrading numerical stability, cu…
arXiv:2609.39357v1 Announce Type: new Abstract: Asynchronous SGD is a popular algorithm for distributed learning where each client's gradient update i…
arXiv:2609.39340v1 Announce Type: new Abstract: Electrolyte formulation design requires balancing multiple physicochemical properties, yet existing mo…
arXiv:2609.39338v1 Announce Type: new Abstract: Knowledge distillation transfers knowledge by encouraging a student to match a teacher's predicted cla…
arXiv:2609.39337v1 Announce Type: new Abstract: Self-supervised pre-training of time series models is currently dominated by next-token prediction and…
arXiv:2609.39336v1 Announce Type: new Abstract: Understanding the fundamental mechanisms of learning is essential for designing systems with strong ge…
arXiv:2609.39329v1 Announce Type: new Abstract: Long-context inference with Large Language Models (LLMs) is bottlenecked by the linearly growing memor…
arXiv:2609.39321v1 Announce Type: new Abstract: Group Relative Policy Optimization (GRPO) has emerged as a memory-efficient reinforcement fine-tuning…
arXiv:2609.39306v1 Announce Type: new Abstract: Iterative self-distillation enables LLM agents to learn from successive deployments, offering a path t…
arXiv:2609.39296v1 Announce Type: new Abstract: Video semantic communication has attracted increasing attention as a promising approach to improving v…
arXiv:2609.39291v1 Announce Type: new Abstract: Physics-informed computational methods usually optimize parameters within a functional representation…