Evaluation of VOiLA on three benchmark problems indicates that VOiLA achieves equal or better performance than current reinforcement learning methods for POMDPs, while using less than 10% of the training data, and generalizes much better to unseen environment configurations.
Marcus Hoerger, Rishikesh Joshi, Rahul Shome et al.· arXiv.org· 0 citations
ANEForge is a Python package that programs the Apple Neural Engine (ANE), the fixed-function neural accelerator on every recent Apple device, directly and without CoreML. In production the engine is reachable only through CoreML, which treats it as a scheduling option: no configuration requires the ANE, and a model can...
Post-training LLM pruning relies on a small calibration set, usually chosen heuristically and judged by WikiText perplexity or by mean accuracy on general-domain commonsense benchmarks. This single-axis view hides capability-specific effects: at 60\% sparsity, strategies separated by $2.85$ points in averaged commonsen...
Hu Xu, Zhaolong Xing, Congcong Liu et al.· 0 citations
Video multimodal large language models (MLLMs) have made rapid progress in general and long-form video understanding, yet their ability to capture and use brief, answer-critical visual evidence remains underexplored. Momentary actions or state transitions may determine an answer while occupying only a small fraction of...
Xiaolin Liu, Yilun Zhu, Xiangyu Zhao et al.· 0 citations
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The pretraining data mixture of Large Language Models (LLMs) constitutes their "digital DNA", shaping model behaviors, capabilities, and failure modes. Yet this composition is rarely disclosed, making post-hoc auditing of data combination or provenance difficult. In this work, we formalize Data Mixture Surgery (DMS): g...
Yaxin Luo, Jiacheng Cui, Xiaohan Zhao et al.· 0 citations
Standard accuracy on binary reasoning benchmarks hides critical failure modes: prior collapse, inconsistency under paraphrase, and inability to reason about parameter-dependent dynamics. We present ChaosBench-Logic v2, a 40,886-question benchmark over 165 dynamical systems with 27 FOL predicates and 78 axiom edges, tog...
EEG-based visual decoding aims to establish a mapping between neural signals and visual semantics. However, it remains constrained by the dual challenges of severe information granularity mismatch and the low signal-to-noise ratio (SNR) of EEG signals. Existing approaches typically treat visual features as static, igno...
Fan Yin, Chuhang Zheng, Peiliang Gong et al.· 0 citations
Language-based agent control is introduced, a new programming model for agentic applications that brings techniques from programming languages and language-based security to the problem of agent control by requiring agents to generate programs that are themselves well typed in the context of the surrounding scaffolding...
Reinforcement learning agents for portfolio management are typically trained and deployed as static policies, with no mechanism for policy adjustments using price forecasts at inference time. We propose FinPILOT (Financial Plugin Inference-time Learning for Optimal Trading), a plugin inference-time policy optimization...
Large language models (LLMs) can learn new tasks through fine-tuning, but learning tasks sequentially often leads to catastrophic forgetting of earlier ones. This paper proposes CRAFT, a continual learning framework that keeps model weights frozen and instead learns low-rank interventions on hidden representations. Sim...
Md Anwar Hossen, Fatema Siddika, Juan Pablo Munoz et al.· 0 citations
Large language models (LLMs) face diverse privacy threats, yet existing studies typically evaluate individual attacks in isolation, offering limited guidance on which system factors drive privacy vulnerabilities. This paper presents a unified threat model and a systematic ablation study of four representative attacks:...
Karima Makhlouf, Lamiaa Basyoni, Syed Khaderi et al.· 0 citations
Vision-Language-Action Models (VLAs) inherit their visual and linguistic capabilities from Vision-Language Models (VLMs), yet most VLAs are built from off-the-shelf VLMs that are not adapted to the embodied domain, limiting their downstream performance. In this work, we propose EmbodiedMidtrain to bridge the gap betwee...
Yiyang Du, Zhanqiu Guo, Haochen Zhang et al.· 0 citations
