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Monday 19 October
- PaperA Pitfall in the Evaluation of Gene Perturbation Models
Gene perturbation models aim to predict transcriptional responses to unseen genetic interventions, but comparisons rely on heterogeneous evaluation metrics and differenti
- PaperExploration via Activation-Space Steering for Reinforcement Learning with Verifiable Rewards
Reinforcement learning with verifiable rewards (RLVR) trains a language model by sampling responses, scoring them with an automatic verifier, and updating the policy from
- PaperDynamics-Aware Sparse Attention for Efficient Autoregressive Video Diffusion
Autoregressive Diffusion Transformers have emerged as a powerful paradigm for long video generation. However, they are often constrained by prohibitive computational over
- PaperREFLEX: RNA Ensemble Generation via Flexibility-Calibrated Stochastic Bridge
RNA molecules often function through multiple experimentally observed conformational states. A central challenge is to capture ensemble diversity without sacrificing stru
- PaperAudioScorer: Learning Question-Aware Token Relevance for Large Audio Language Models
Large Audio Language Models (LALMs) reason over speech, environmental sounds, music, and other acoustic information. However, their audio encoders produce dense token seq
- PaperLOCU: Lowdin-Orthogonalized Constraint Updates for Multi-Constraint Policy Optimization
We investigate multi-constraint policy optimization in constrained Markov decision processes (CMDPs), where interactions among constraint gradients often yield ill-condit
- PaperXGLASS: X-Ray, Gaze and Language Assisted Slice Sequencing for CT Volumes
Vision-language models (VLMs) achieve remarkable performance on 2D medical images, such as X-rays or pathology images, while 3D VLMs that directly process CT/MRI volumes
- PaperSEAM: Spectral Embedding Alignment and Merging for Low-Resource TTS
Expanding the vocabulary of conditional text-to-speech (TTS) models typically requires extensive fine-tuning with paired audio, creating a major bottleneck for low-resour
- PaperBeyond Static Leaderboards: Capability-Focused Evaluation with Structural Diversity for Time Series Foundation Models
Static public benchmarks for time series foundation models (TSFMs) typically have fixed and narrow test distributions. Their repeated reuse encourages benchmark-specific
- PaperRECAP: Reciprocal Sparse Attention and Hierarchical Caching for Efficient Video Diffusion
Diffusion transformers generate high-quality videos but remain computationally expensive. Sparse attention and temporal caching reduce computation within and across denoi
- PaperMachina Pauliana: A neuro-symbolic approach to the actio pauliana in Dutch insolvency law
Applying a legal provision frequently requires both structured rule-based reasoning and sensitivity to open-textured terms developed in case law. The actio pauliana of Ar
- PaperCoRS: Fast Neural Flexible Job-Shop Scheduling via Composite Interval State Reuse
Neural solvers for the Flexible Job-Shop Scheduling Problem (FJSP) typically refresh graph representations and update feasibility after every operation--machine decision.
- PaperShaping the Document, Not the Model: Optimized Suffixes for Context Following
When a user supplies a document and wants the answer drawn from it, a language model is expected to follow it even when it contradicts its parametric knowledge. Prior wor
- PaperHeartbeat Thinking: Speculative Reasoning and Tool Execution While Listening in Realtime Voice Agents
Tool-using voice agents often leave users waiting after speech ends, even when actionable information arrives earlier in the request. Speculative approaches begin work du
- 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
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.