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Sunday 18 October
- PaperWhen Form Changes but Logic Doesn't: Building Logic-invariant LLMs through Logical Structure
Large language models (LLMs) have achieved strong performance across diverse reasoning tasks, yet it remains unclear whether this performance reflects an understanding of
- PaperRAHF-Net: Range-Aware Heterogeneous Fusion for LiDAR-Assisted RGB Semantic Segmentation
This paper studies LiDAR-assisted RGB semantic segmentation, where LiDAR point-cloud features improve dense pixel-wise predictions in the RGB image plane rather than 3D p
- PaperFrom Unverifiable Domain Text to Cross-Lingual RLVR via Code-Switched Task Synthesis
Reinforcement Learning with Verifiable Rewards (RLVR) can improve reasoning in large language models, but specialized non-English domains expose a data mismatch. Raw Engl
- PaperPolarVis: A Dataset and Diffusion Framework for RGB-to-Polarization Perception in Adverse Driving Scenes
Reflections, glare, transparent structures, and material-dependent appearance variations can introduce ambiguity into RGB-based visual perception in vehicle-relevant envi
- PaperA 3D-Driven Framework for Moving-Camera Perspective-to-360° Video Generation
Turning a moving-camera perspective video into a 360° video requires more than just generating content outside the input frame: observations revealed over time must be pr
- PaperPaloma: Phase-Conditioned Residual Modulation for Time Series Forecasting
Explicitly modeling periodicity has proven to be an efficient approach for time series forecasting, where the residual, obtained after removing the periodic component fro
- PaperATLAS: Attention-Guided Test-Time Latent Selection for Compositional Visual Autoregressive Generation
Visual autoregressive models produce convincing images but can misassign attributes and spatial relations. Searching multiple generation paths can improve composition, ye
- PaperThe Hidden Look-Ahead: Point-in-Time Leakage in Electricity Market Data
Empirical studies of electricity prices routinely state that their models use only information available at the time of the trading decision. For weather-driven forecasts
- PaperOnly Means Only: what a harmonization benchmark score averages over
Image harmonization methods adjust the colour and lighting of an object pasted into a photograph so that it looks native to its new scene, and they are ranked by average
- PaperStructured Relevance Determination and Channel Additive Gaussian Processes for Image Data
We introduce radial basis function (RBF) kernels for Gaussian processes that use structured hyperparameter sharing for image-valued inputs. For high-dimensional inputs su
- PaperOutcome-Anchored Credit Reallocation for Agentic Knowledge Graph Question Answering
Agentic knowledge graph question answering (KGQA) requires large language models (LLMs) to solve complex questions through multi-turn interactions with a knowledge graph
- PaperWhen Weak Submodularity Meets Matroids: How Does Standard Greedy Behave?
Weakly submodular maximization finds numerous applications in machine learning, data mining and statistics. In particular, under a cardinality constraint, the standard gr
- PaperSimulating Infant Senses with Age-Tuned Networks
What a newborn sees, hears and feels, and how this changes month by month, has been measured sense by sense, with different methods and in different units. We bring these
- PaperTILDE: Teacher-in-the-Loop Distillation from Embodied Foundation Models
Large-scale action pretraining equips Embodied Foundation Models (EFMs) with strong manipulation capabilities, with particular strengths in generalization and closed-loop
- PaperMining the Self-Rewriting System: A Vision for Data Mining on AI-Native Infrastructure
Classical data mining treats data as generated outside the learner. Emerging AI-native infrastructure invalidates this assumption: as agents observe system state, act, up
- PaperMemDerive: A Diagnostic Benchmark for Agent Memory over Evolving Data
Long-running agents rely on memory of their past interactions for task state, such as what has been completed and which conditions still hold. Such state is usually a der
- PaperWhistle and Wrong Lyrics: Synthetic Queries Are Not Enough for Real-World Query-by-Melody
People look up a song by humming it, but also by whistling it or singing it with the wrong words. Published query-by-humming systems and benchmarks focus on hums and sung
- PaperMulti-site Learning for Forecasting Day-Ahead Wind-Power Production for Onshore Wind Farms in Great Britain with Deep Neural Networks
Accurate day-ahead wind-power production forecasting is increasingly important for energy system operations, market activity and balancing Great Britain's grid as wind ge
- PaperPainting Change Map as guidance for generating painting processes
Digital art generation has undergone a massive paradigm shift, moving from static image synthesis to dynamic video generation that can mimic the human painting process. W
- PaperGreenNIDS: A Benchmark Workflow and Analysis Dataset for NetFlow Intrusion Detection Experiments
Comparing the predictive performance and computational cost of flow-based intrusion detection experiments requires both quantities to be available for each run. GreenNIDS
- PaperAligning Cultural Behaviors in Arabic Language Models via Preferences
Arabic LLMs have improved rapidly, but aligning them with country-specific cultural behavioral preferences remains underexplored. Previous work has focused primarily on i
- PaperOperator-Mismatch Contrastive Learning for World-Relative Trajectory Coherence
World models are increasingly judged by how well they rank plausible futures, yet plausibility alone is the wrong target. The same scene can evolve under many latent rule
- PaperCD-OPD: Contextual Digest for On-Policy Distillation
Teacher takeover in on-policy distillation (OPD) can produce incorrect responses even when the student and teacher independently answer the same problem correctly, a fail
- PaperLateMatch: Breaking the Interaction Bottleneck via Cacheable Matching for Efficient Visual Localization
Visual localization is critical for embodied agents, but deploying state-of-the-art deep feature matchers on edge devices is fundamentally limited by their massive comput
- PaperCHSM8: A Chess Transformer that Follows Natural-Language Style Prompts
We present CHSM8, a 210M-parameter chess transformer that plays moves conditioned on a free-text description of a playing style, e.g. "go for the Sicilian Defense", "soli
- PaperLocal Evidence, Global Failure: Diagnosing Speech-Vision Temporal Composition in Audio-Visual Language Models
Audio-visual large language models (AV-LLMs) can fail at full-video speech-vision decisions even when useful visual evidence is locally recoverable. We introduce Temporal
- PaperWhen Planning Problems Become Hard for LLMs: Separating Structural Complexity from Semantic Interpretability
Large language models (LLMs) struggle with classical planning, but benchmarks rarely distinguish structural difficulty from the difficulty of interpreting symbolic vocabu
- PaperPredicted Class Correction: Conformal Thresholds for Classes with No Calibration Data
Class-conditional conformal prediction calibrates a separate score threshold for every class and therefore requires labelled calibration examples of every class. In long-
- PaperMCSplat: Multi-View Photometric and Geometric Consistent Feed-Forward Gaussian Splatting for Driving Scenes
Driving-scene reconstruction via feed-forward Gaussian splatting from sparse multi-view images remains challenging due to two factors. First, cross-camera photometric inc
- PaperFoundPDE: A generative foundation model for data-driven symbolic discovery of partial differential equations
Discovering governing partial differential equations (PDEs) from observed data is a central inverse problem in computational science and engineering: the goal is not only
- PaperCASE: Complementary Articulation-Aware Speech Encoder to Enhance Speech-Driven 3D Facial Animation
General-purpose self-supervised speech encoders provide strong acoustic representations, but their pretraining objectives are not explicitly aligned with the visible arti
- PaperFormally Verified Autoresearch for Analyzing the Expressivity of Multi-Head Attention
Multi-head attention is a central component of the transformer architecture, yet how its expressivity depends on the number of heads remains poorly understood. We study a
- PaperEdge Deployable Lightweight Framework for Real-Time Driver Safety System with Integrated Lane Departure and Traffic Sign Recognition
Lane departure and traffic-sign negligence are leading contributors to road accidents, particularly in regions with non-standardized signage and limited annotated data. E
- PaperA Distribution-Free Separation Between Learned and Fixed Features
The success of neural networks is largely attributed to their ability to learn useful representations from training data. However, known results that prove a computationa
- PaperCoRe-WM: Conditioned Response-State World Modeling for Longitudinal Treatment-Response Prediction in Breast DCE-MRI
Pathologic complete response (pCR) after neoadjuvant chemotherapy is a key prognostic indicator in aggressive breast cancer, yet existing prediction approaches either rel
- PaperFollow the Mixed Groups: Ridge-Tracking Gaussian Sampling for Zero-Variance Web Rollouts
Group relative policy optimization learns from a question only when the sampled responses disagree. A group that is entirely correct or entirely incorrect has zero reward
- PaperMPIG: Multi-angle Polarization Image Generation from a Single Polarization Observation
Polarization imaging provides informative cues for material analysis, scene understanding, and visual perception. However, acquiring complete polarization observations ty
- PaperWhere Groups Split: A Probe Prior for Nonzero Within-Group Variance in RL Post-Training
Group relative policy optimization learns from a prompt only when the rewards in the sampled group disagree. With a binary verifier, a group that is entirely correct or e
- PaperWhere and Why Search-Augmented LLMs Fail When Reasoning over Rapidly Evolving Knowledge
As the world changes, new information is published while older records remain online. This complicates reasoning for large language models (LLMs), which must retrieve evi
- PaperAdaFedXplain: Adaptive Federated Learning with Explainable AI for Ransomware Detection
Attacks using ransomware have developed into complex multiphase campaigns that target vital infrastructure, resulting in annual damages of billions of dollars. Convention
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.