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Newest papers, page 144
Recursive Code Evolution for Task-Oriented Semantic Communications
Semantic communication jointly optimizes inference accuracy, channel use, and computation, yet the underlying communication program is typically specified before training.Probabilistic Machine Learning for Short-Term Atmospheric Seeing Forecasting
Accurate short-term forecasting of atmospheric seeing is of significant interest for astronomical observations and free-space optical communication systems, where rapid variations in optical…SPARE: Sparsity Allocation via Routing Entropy for Efficient MoEs
Mixture-of-Experts (MoE) architectures scale model capacity efficiently, yet their substantial memory footprint poses a major barrier to deployment.Lineage-Aware Search Control for LLM-Based Evolutionary Factor Mining
Formulaic alpha factor mining searches for symbolic expressions that transform market data into predictive signals.Leveraging Time-Series Foundation Models for Financial Crime Detection
Financial crime detection requires identifying illicit activity within large transaction networks, where suspicious behaviour is rare and unfolds over time.Characterizing Oblivious Common-Reward Multi-Player Bandits: Universal Stationarity, Coordination Traps, and Certified Global Rates
This paper presents a theoretical analysis of the oblivious common-reward multi-player multi-armed bandit (OC-MPMAB), a minimal multi-player bandit model in which multiple players select arms…DriveMLP: When Training Strategy Outperforms Model Complexity in Autonomous Driving
Learning motion planning policies that remain reliable under closed-loop execution is a central challenge in Autonomous Driving (AD).Lifting PCA in the Wasserstein Space
Principal Component Analysis (PCA) is a fundamental tool for statistical dimension reduction, yet no canonical extension to distribution-valued data has emerged within the framework of optimal…TraceForge: Distilling with Your Own Thinking
Using an LLM to generate training data for another is among the most general ways to train one, and it remains common practice.Rethinking Post-hoc Debiasing of Large Pretrained Models
Large pretrained models such as CLIP are widely used as frozen feature extractors.Structure-Aware Message Passing on Petri Nets through Directed Walks and Incidence Diffusion
A common application of the process mining discipline is to connect observed event data with Petri nets, which are bipartite, directed graphical process models with rich formal underpinnings.Post-hoc Epistemic Uncertainty for Vision-Language-Action Policies
Vision-language-action (VLA) policies need to recognize gaps in their training knowledge to request useful demonstrations or assistance in new situations, especially when failures are costly.Monitorability Is Trainable: Post-Training for Chain-of-Thought Monitorability
Chain-of-thought (CoT) monitoring is one of the few practical tools available for overseeing capable AI systems, but it is fragile: a model's reasoning is only useful to a monitor if it remains…Where Do LLMs Learn to Recommend AI?
Asked what to study, which career to pursue, or what product to build, large language models (LLMs) often recommend AI-related options.Asymmetric Likelihood-Free Hypothesis Testing
In likelihood-free hypothesis testing (LFHT), given samples from two unknown distributions $P,Q$ on $[n]$ with $\mathrm{d_{TV}}(P,Q)\geq\varepsilon$, and from a third distribution $D\in\{P,Q\}$, the…Real PMIDs, Wrong Papers: Harness Design for Biomedical Claim-Verification Agents
Literature-searching language agents are becoming a standard component of scientific assistants for the life sciences, yet there is little controlled evidence on which parts of their harness matter.NeuroCodec: EEG-Guided Latent-Domain Generative Model for High-Fidelity Target Speaker Extraction
Driven by recent advancements in hearing assistive devices, target speaker extraction (TSE) in multi-talker environments has drawn significant attention.RangeNav: Task-Aligned LiDAR Range-Image Pretraining for Robot Navigation
Autonomous mobile robots operating in dense crowds and cluttered sites require $360^\circ$ perception to react to surrounding hazards.Silent Alignment in Two-Layer Linear Networks: A High-Dimensional Perspective
We study gradient flow in a two-layer linear network in the high-dimensional regime where the input, inner and output dimensions diverge proportionally.A Sharp Dynamic Haussler Lemma
Haussler's covering lemma (JCTA 1995) gives the sharp $(C/δ)^d$ metric-entropy bound for binary VC classes under normalized $\ell_1$ distance.