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Monday 19 October
- PaperTowards More Granular Reasoning: Mapping the DSA Transparency Database Taxonomy to Platform Terms and Conditions Using Large Language Models
Article 24(5) of the Digital Services Act (DSA) requires providers of online platforms to submit every content moderation decision they make, with a corresponding Stateme
- PaperRethinking BPE: Merge Selection as Model Selection
Subword tokenization methods such as Byte-Pair Encoding (BPE) are a core component of modern language models; yet, tokenizer capacity remains typically determined by a fi
- PaperSAR2Net: Learning Spatially Anchored Representations for Retrieval-Guided Cross-Stain Alignment
Achieving spatial alignment between whole-slide images(WSIs) across stains is essential for integrating morphology and molecular information, yet it remains challenging d
- PaperRoAR-VAE: Improving Latent Diffusability through Robust Prediction
An effective visual tokenizer must preserve image fidelity while producing latents that downstream diffusion models can learn efficiently. Prior work improves latent diff
- PaperFairness or Fallacy? Mapping the Landscape of AI Bias in Disease Detection
Artificial intelligence (AI) has several transformative effects on healthcare, like to facilitate clinicians in disease detection and to manage patient care with enhanced
- PaperExMR: Extremity Motion Refinement for Monocular Human Motion Capture
Detailed hand and foot articulation is important for animation and motion analysis, yet remains challenging to recover from monocular video. Recent expressive video metho
- PaperLLMs Prompted for Legal Context Refuse More: Overrefusal from Small On-Premises LLMs in Criminal Legal Context
Confidentiality requirements increasingly push legal professionals toward small, on-device LLMs that keep case data in-house, used for everyday tasks such as summarizatio
- PaperOceanTensorCube and ST-MMT: A Multimodal Data and Transformer System for Seven-Day Forecasting of Pyropia Bleaching
Bleaching of cultured Pyropia (laver) causes losses in Korean seaweed farming. We present a system that forecasts bleaching seven days ahead for farm clusters. OceanTenso
- PaperFocused Omni-Modal GUI Agents
Graphical User Interface (GUI) agents increasingly act over streaming omni-modal observations spanning screenshots, audio, video, interaction history, and device states.
- PaperTaQFormer: A Treatment-as-Query Transformer with Data-Fusion for Multidimensional Treatment Modeling in Coupon Allocation
We study coupon allocation on an online marketplace offering multiple service categories. Issuing coupons requires choosing a vector of category-specific discounts, accou
- PaperGeoEdit: Adversarial De-Evidencing for Silent Geoprivacy Protection via Image Editing
Recent efforts have demonstrated the strong capabilities of Multimodal Large Reasoning Models (MLRMs) in geographic reasoning. By jointly analyzing subtle visual cues, th
- PaperRobust Latent Variable Graphical Models: Exact Recovery and Fundamental Limits
We study robust estimation of a Gaussian precision matrix that decomposes as a sparse matrix minus a symmetric, possibly indefinite, low-rank matrix, a structure that ari
- PaperVEILED-SH: Vulnerability Expression through Indirect Language Evaluation Dataset (Self-Harm)
AI systems may miss indirect, culturally situated distress or provide support mismatched to the application context. Existing benchmarks do not jointly address cultural v
- PaperWan-Alpha++: Animating a Single RGBA Asset into Controllable Transparent Video Effects
RGBA video generation is essential for creating compositable visual assets in filmmaking, game development, and digital content production. However, generating high-quali
- PaperOn Counting Graphs for Modal Logic with Counting
In this paper, we study the theoretical computational complexity of counting trees and graphs that are classified positively by a graph neural networks, or said equivalen
- PaperMoveBench: A Rubric-Based Benchmark for Evaluating Large Language Models in Sports and Health Coaching
Despite rapid advances in large language models (LLMs), their deployment in the sports and health domain remains high-risk due to the absence of domain-specific evaluatio
- PaperHP-PnP-Flow: Hybrid Time Scheduling and Projection for Plug-and-Play Image Restoration via Flow Matching
Image restoration is a fundamental inverse problem that seeks to recover high-quality images from degraded observations. Plug-and-Play (PnP) methods provide a flexible fr
- PaperReading Time Modeling with Pixel-Based Language Models
Tokenization-free, pixel-based language models (PLMs) have recently been proposed as an alternative to conventional token-based language models (TLMs), typically motivate
- PaperLearning Goal-Conditioned Subgoals through Frozen Hierarchical World Models
Hierarchical world models plan over long horizons by passing predicted states from a coarse model to a lower-level controller. Choosing these states can be expensive: the
- PaperConditional information Retrieval for Longitudinal Survey Harmonisation
Identifying conceptually equivalent questions across different surveys is a challenging information retrieval task where surface-level textual similarity is insufficient.
- PaperVISAGENT: An Agent-Based End-to-End Voice Interaction System
Voice-based public services have evolved from manual switchboards to intelligent platforms to meet modern user needs. However, current systems remain constrained by rigid
- PaperTriTD: Tri-Partite Trajectory-Distribution Distillation for Real-Time Autoregressive Video Generation
Autoregressive (AR) video diffusion has emerged as a leading paradigm for efficient video generation, yet its practical deployment remains bottlenecked by the trade-off b
- PaperDynamical Batching: How Class-Cycling Training Shapes the Internal Structure of Neural Networks
We investigate whether cyclically varying the class composition of training batches can modify both the performance and the internal organization of neural networks. Moti
- PaperDeepSEA: A Multilingual Evaluation Benchmark for Southeast Asia
While language models have demonstrated remarkable capabilities, their performance remains disproportionately skewed towards high-resource languages. This disparity is pa
- PaperPhysics-Driven Framework for QoS-Constrained Satellite System with Non-Linear PA Distortion
This work develops a physics-driven self-supervised graph learning framework that directly optimizes the distortion-aware precoder under nonlinear correlated power amplif
- PaperFLMNet: Self-Ensemble Distillation from Masks to Seeds for Single-Tower CTR Prediction
Click-through rate (CTR) prediction underpins recommender systems and online advertising, where high-dimensional categorical features interact in combinatorially many way
- PaperReinforcement Learning Controllers for Fusion Scenario Development
Scenario development, the design of the waveforms that take a tokamak discharge from breakdown to flat-top, is still an iterative, labour-intensive process. Every candida
- PaperNash-MOPD: Optimizing Task Trade-offs in Multi-Teacher On-Policy Distillation
Multi-teacher on-policy distillation (MOPD) aggregates the capabilities of multiple domain-expert teachers into a single student model. However, all domains in MOPD share
- PaperOptimal Multi-Kernel Combination for Online Multi-Label Classification
Multi-label classification is particularly challenging in streaming scenarios, where data arrives sequentially. Online kernel methods offer a promising solution. However,
- PaperVariance-Aware Non-Stationary Bandits:All-Budget Regret Bounds and Adaptation Costs
Low reward variance reduces estimation cost, but does not eliminate monitoring of arms that may improve while unobserved. We refine the variance--variation tradeoff and c
- PaperFrom Retrieval to Recognition:Knowledge-Enhanced Post-training of Time Series Foundation Models for Classification
Time series foundation models (TSFMs) have achieved notable progress in classification tasks through large-scale pretraining. However, their post-training practice mainly
- PaperDon't Rewrite the SID Map: Topology Preservation for Generative Retrieval in Dynamic E-Commerce Search
Generative retrieval assigns each item a discrete semantic identifier (SID) and retrieves items by autoregressively generating SID sequences. In dynamic environments such
- PaperDeclarative Explanations for Graph Neural Networks: A Demonstration
Graph Neural Networks (GNNs) have proven effective for graph analytical tasks, yet their "black-box" nature complicates the understanding of their layer-wise behavior and
- PaperLearning from a Bandit Learner
Classical inverse bandit methods typically aim to recover true reward parameters. In contrast, we infer a demonstrator's subjective beliefs, specifically its internal est
- PaperProvable Adversarial Detection: Prime Quantization meets Gromov--Wasserstein
Adversarial vulnerability persists across modern vision architectures from CNNs to vision language models (VLMs), yet existing detection methods rely on heuristics withou
- PaperReliable Before Profitable: QuantHarness for Governing Financial Strategy Development with LLM Agents
LLM agents can turn natural-language financial research requests into executable and backtested strategies, but a successful run may still implement the wrong rule, use i
- PaperMultilingual Voicemail and Answering Machine Detection via Pretrained Audio Embeddings and Gradient Boosting Machines
Answering machine detection (AMD) is a fundamental task in telephony that classifies whether an answered call is picked up by a human or a voicemail (machine). Despite it
- PaperFrom Code to Playable Systems: CEGame-Bench for Long-Horizon Game Creation Agents
A game ships when a player can launch it, finish it, and return to a saved world, none of which a successful build guarantees, yet game-creation agents are mostly tested
- PaperPnP-Transformer: A Neural Pose Solver for Zero-Shot 6D Object Pose Estimation
We present PnP-Transformer, a neural pose solver designed as an iterative-free, differentiable alternative to classical PnP-RANSAC algorithms. PnP-Transformer regresses t
- PaperHow Robust Are Prognostic Radiomic Features? Comparing Selection Techniques on Pooled Glioblastoma Cohorts
Radiomic survival studies in glioblastoma report heterogeneous prognostic features, but how much of this stems from the methodology itself is rarely examined. We analysed
Headlines and links come from the labs' own blogs, Hacker News and the GDELT news index, and from the sources our index already follows. We show a short excerpt and always link to the original. A launch reported by a news site rather than the lab is marked “Reported” until the lab itself announces it.