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…
nlp
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RAG
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記事一覧
16 / 37Uni-Mem: Learning a Long-Horizon Agentic Memory Manager with Unified Online Policy Optimization
Long-term agent memory is shifting from predefined workflows toward learnable policies for memory construction and retrieval. Existing learning-based methods either optimize construction alone or…
math-theory
Joint-Angle Invariance of Jacobian-Based Performance Indices for Serial Robotic Manipulators
This article investigates the joint-angle invariance (JAI) of Jacobian-based performance indices for serial robotic manipulators. We identify kinematic conditions under which representative…
nlp
Distance Field Driven Reinforcement Learning for Reactive and Robust Collision Avoidance
Robust and reactive collision avoidance remains a central challenge for deploying Reinforcement Learning (RL) policies on real robotic manipulators, particularly when transferring behaviours learned…
nlp
Region-Aware Multi-View Inspection Using Deep Learning and Domain-Informed Decision Fusion
Automated optical inspection of precision components with tiny surface defects remains challenging when different regions of the same component exhibit different defect characteristics and,…
nlp
C$^2$U in RAG: Compositional Concept Unlearning in Retrieval-Augmented Generation
Retrieval-augmented generation can expose unwanted concepts through retrieved evidence even when the generator is moderated. We study query-side concept suppression with a fixed encoder and document…
nlp
Pricing Information in Search with Nonobligatory Inspection
As AI agents reshape Web search and advertising, platforms can monetize information that improves decisions. We study information pricing for sequential search among independent alternatives with…
machine-learning
ChroNoC: A Tableless TDM Circuit-Switched NoC With Delay-Aware Deployment for Time-Sensitive Neuromorphic Computing
Time-sensitive neuromorphic architectures require predictable interconnects to preserve precise event timing. Statically scheduled time-division-multiplexed (TDM) circuit-switched networks-on-chip…
deep-learning
One Policy, Many Styles: Where to Aggregate Preferences for Steerable Humanoid Control?
Modern robotic agents are increasingly expected to support steerable control, where a single policy can adjust its behavioral style at runtime under changing user preferences. Preference-conditioned…
nlp
Borrowing Strength Across Stores: Transfer Learning for Choice-Based Revenue Management
Large retail chains must tailor assortment and pricing decisions to local customer preferences, yet even retailers with extensive sales records often have limited data for estimating demand at the…
nlp
Predicting silent failures of learned inference under restricted access: what measurement physics and prior information explain
Learned priors are used to reconstruct regions that measurements barely reach, and to report uncertainty there. They can fail silently: the reported interval excludes the truth while every…
nlp
Near-Optimal Regret Bounds for UCB-Style Gaussian Process Bandits via Data Thinning
Gaussian process upper confidence bound (GP-UCB) has been widely studied, though its known regret upper bound is suboptimal. To obtain near-optimal regret upper bounds, existing studies mainly focus…
nlp
Practical Advantages of Online Conformal Prediction for Data Streams
Full conformal prediction offers finite-sample marginal coverage guarantees under exchangeability, but exact computation can be costly, while its classical guarantees do not directly extend to…
nlp
Elucidating the Design Space of LM Data Attribution
Data attribution methods for Language Models (LMs) are typically evaluated using downstream tasks like fact retrieval. However, existing evaluations vary multiple dataset properties simultaneously,…
nlp
Luggage re-identification: A study of strategies towards a real-world application
Luggage re-identification (ReID) is a critical task in video surveillance for forensics, security or border management (suspicious or abandoned luggage recognition), as well as luggage management…
nlp
SymAnt: Grounding Long-Horizon Action Anticipation with Adaptable Symbolic Priors
As robots and intelligent systems increasingly interact with humans, they must anticipate long sequences of future actions from only brief observations. While purely neural models typically require…
deep-learning
Gym-Anything for Robotics: Scaling physical simulations with digital agents
Realistic, fast robotics simulations could enable large-scale training of embodied AI models that transfer to the real world. However, despite decades of progress, available simulations cover only a…
nlp
Retrieval as Traversal: Value-Indexed Memory for Stateful Long-Context Agents
Long-context models repeatedly solve closely related retrieval problems. Attention or global retrieval can retain large stores, but each forward pass again searches for what matters.
deep-learning
CrossWeave: Cross-Modal Scene and Instance Retrieval from Sparse 2D-3D Alignment
Cross-modal scene and instance retrieval aims to retrieve a corresponding 3D environment or object given query 2D images, serving as a foundational mechanism for spatial reasoning in robotics and…
computer-vision
IndicIPR-QA: A Benchmark for Extractive Question Answering on Indian IPR Laws
Legal Question Answering (QA) over statutory texts is a challenging task in Natural Language Processing (NLP), especially in low-resource settings with complex legal systems. It requires answers that…
deep-learning
LucidLyra: Feed-Forward Generative 3D Scene Reconstruction and Joint Understanding via Multi-Task Distillation
We present LucidLyra, a framework that makes generatively reconstructed 3D scenes directly queryable for semantics and instances in a feed-forward manner from video latents. While generative 3D…
deep-learning
AVPS-360: A Spatial Audio-Visual Benchmark for Instance Segmentation and Tracking of Sound-Producing Persons
Audio-visual instance segmentation (AVIS) segments and tracks individual sound-producing objects in videos. Existing benchmarks predominantly use monaural audio, which lacks inter-channel cues for…
nlp
Soil Moisture Estimation in Precision Agriculture: A Knowledge Distillation Approach
Accurate soil moisture estimation is critical for precision agriculture, influencing irrigation, fertilization, and harvesting strategies. Traditional methods primarily rely on meteorological and…
deep-learning
NECA: Neighbor Event Curve Augmentation for Multi-Horizon ICU Deterioration Prediction
Early prediction of ICU organ dysfunction events supports timely clinical monitoring and intervention, but estimating short-term organ-specific risk from early ICU records remains challenging due to…
nlp