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Friday 16 October
- PaperAlliance of Stochastic Routing and Reinforcement Fusion for Multi-Model Reasoning
This paper studies dynamic model routing under uncertainty in multimodal settings, where a system must select and potentially compose multiple models to answer a query. S
- PaperMTEdit: Packed Trajectories Beat Rollouts for Multi-Turn Image Editing
Multi-turn image editing aims to modify an image according to a sequence of instructions, making it better aligned with human-AI collaborative creation than single-turn e
- PaperBeyond Multi-Stage Pipelines: A Label-Correlation Ensemble for Multi-Label Retinal Fundus Disease Classification
Retinal fundus images frequently carry more than one disease, and public fundus datasets are heterogeneous and severely long-tailed. Clinical triage suggests a staged des
- PaperVocalGrad: Evaluating Acoustic Perception in Audio Language Models
Recent large audio language models (LALMs) have extended their capabilities beyond lexical speech understanding to tasks requiring paralinguistic and non-linguistic audio
- PaperThe Italian lawmaking process: a unified and structured dataset
The Italian legislative process is documented in detailed parliamentary records hosted in institutional websites. However, much of this information is available only as u
- PaperLagNet: Lag-Structured Operators for Long-Term Time Series Forecasting
Long-term time series forecasting maps a finite history window to an extended future horizon. Many existing models focus primarily on the design of input representations
- PaperBridging the Language Gap in Scholarly Data II: Enhancing Gender Inference for Chinese Names
Perceived gender inference from names is important for inclusive scientometrics research, yet existing methods perform poorly on non-Western scholars. We address this gap
- PaperSynthetic Image Oversampling for Rare-Class Representation Learning in Deep Facial Phenotyping
Recent deep facial phenotyping methods can support the recognition of genetic syndromes, but patient images are often scarce and unevenly distributed across disorders. Sy
- PaperEscaping Parameter Space: Tight Generalization Bounds via Representation Quality
We derive a tight generalization bound for deterministic neural We derive a tight generalization bound for deterministic neural networks based on their last hidden layer
- PaperECG-SDI: Single-lead Electrocardiogram Enables Continuous Sleep Depth Index Profiling and Scalable Digital Biomarkers for Sleep Health
Conventional sleep staging provides a coarse-grained representation that obscures within-stage depth variation. We developed ECG-SDI, a single-lead electrocardiography (E
- PaperRed-Teaming Multi-Agent Attacks for Loss-of-Control Risks
AI agents are growing more capable and persistent, and are being deployed in ever larger numbers. As more start collaborating, AI control measures must remain effective w
- PaperBeyond Large Language Models: A Mental World Model Framework for Mental Modeling, Simulation, Evolution, and Interpretability
Understanding and simulating how subjective cognition and mental states emerge, evolve, and shape behavior is essential for advancing artificial intelligence toward deepe
- PaperRecognizing Study Lineage Is Not Enough: Over-Crediting Same-Trial Evidence in LLM-Based Medical Verification
Publication count is not study count. A model can identify shared trial lineage correctly in a direct task yet over-credit a second publication from the same trial when a
- PaperNeural Expansion: A Unified Mechanism for How Deep Neural Networks Generalize
Deep neural networks demonstrate remarkable generalization despite being highly over-parameterized, challenging traditional statistical learning theories. While several t
- PaperThe Cognitive Cost of LLM Writing: A Reading-Time Comparison with Human Text
Although linguistic differences between human-written and Large Language Model (LLM)-generated texts have been extensively studied, their implications for the cognitive e
- PaperGLOBE: Evolving Structured Agentic Memory for E-commerce Product Optimization in Generative Search
Optimizing product listings for generative search requires language agents not only to rewrite effectively but also to continually self-improve by retaining successful st
- PaperTool Recommendation for Multi-Step Agents: Finding Every Tool a Task Needs
A multi-step agent task fails when a single tool it needs is missing, yet the tools an agent may need are too many to list: the roughly 8,200 tools on the platform we stu
- PaperFedRAPP: Federated Test-Time Prompt Tuning for Vision-Language Models with Reliability-Aware Prompt Personalization
Federated prompt learning enables vision-language models like CLIP to collaboratively adapt lightweight soft prompts across distributed clients without sharing raw data.
- PaperBlitz: Accelerating the Diffusion Modules of AlphaFold3 and Boltz-2
Diffusion-based protein structure prediction models produce all-atom structures in about 200 denoising steps, and that cost has driven a number of few-step samplers. We p
- PaperVISTA: Steering LLMs with Latent User Values Inferred from a Few Survey Answers
Personalizing a language model requires knowing what a person values, which stays largely consistent across tasks. Yet most methods either learn task-specific preferences
- PaperLogicVal:A Logic-Formalized Benchmark for Constraint Satisfaction in Text-to-Image Generation
Text-to-Image (T2I) generative models have made significant progress in producing high-fidelity images from natural-language prompts. Alongside this progress, numerous be
- PaperEquivalence testing and run-count design for stochastic machine-learning experiments
Claims that two training methods perform equally well often rest on a non-significant difference between two or three runs per method. We develop a protocol, with its pow
- PaperExpressivity of IQP Feature-Map Quantum Kernels via Reproducing Kernel Hilbert Spaces
Quantum kernels are among the most promising methods in quantum machine learning, providing a natural way to embed data into high-dimensional Hilbert spaces via quantum c
- PaperDiscuss More, Comment Less: Boosting Automated Research via Multi-Perspective Collaborative Review
As automated research is increasingly adopted for writing papers, automated review has become a critical link between paper generation and quality control. However, exist
- PaperHardEval: An Execution-Verified Benchmark for AI-Driven Security Hardening and Compliance Remediation
Implementing Security Technical Implementation Guide (STIG) controls remains a demanding operating-system administration task. Each natural-language security requirement
- PaperThe Window Is in the Reasoning: When LLM Agents Decide to Follow Prompt Injections
LLM agents that read untrusted content can be hijacked by prompt injections. Runtime monitors that try to catch a hijack before the agent acts, and benchmarks that score
- PaperBeyond the Benchmark: Conditioning, Domains and Failure Modes of Qwen3-TTS
Qwen3-TTS reports state-of-the-art zero-shot voice cloning, but its technical report leaves open how the model should be conditioned, how it behaves outside read speech,
- PaperAgentic Physics-Grounded Video Generation via Memory-Augmented In-Context Reasoning
Physical plausibility is essential for realistic video generation. Existing methods impose physical guidance before synthesis via simulations or refined prompts, but this
- PaperOn the possibilities and limitations of LLM-based multi-agent systems for multi-criteria decision-making in healthcare operations management
Multi-criteria models for healthcare operations need weights that express how stakeholders trade off patient waiting time, provider workload, and operating cost, but thes
- PaperOwlSight: A Panoramic Monitor for Chain-of-Thought Reasoning
Chain-of-Thought (CoT) monitoring offers actionable evidence for oversight AI systems, with the potential to enable early detection and intervention. However, existing ap
- PaperTUPLE-Bench: Evaluating and Mitigating Privacy-Utility Trade-offs in Typed Decision Models
Typed decision models often return more than a selected category. They also expose probabilities for each candidate and, sometimes, a separate confidence score. These fie
- PaperTriRouter: Sparse-to-Dense Electrode-Space Routing for Robust EEG Motor Imagery Decoding
Motor imagery brain-computer interfaces require reliable decoding from multichannel EEG, but practical acquisition often yields sparse or corrupted electrode montages. We
- PaperPCDFusion: Proposal-Context-Detail Bayesian Rendering for Infrared-Visible Image Fusion
Infrared-visible image fusion (IVIF) aims to combine visible and thermal infrared observations for human perception and downstream vision tasks. Visible and thermal infra
- PaperAn Efficient Approach to Beetle Damage Detection of Banana Using Deep Learning
Visible surface damage of banana fruits by Basilepta subcostata (the banana fruit scarring beetle) can reduce their market value. Here, manual inspection of Banana fruits
- PaperFlexPart: Text-Controlled Semantics-Aware 3D Part Segmentation at Flexible Granularity
A 3D asset admits multiple valid part decompositions, while semantics-aware segmentation should reflect both the desired granularity and the parts a user wants to extract
- PaperA Language-Informed Loss for Visual Generation
End-to-end visual generation with pixel-space loss has recently achieved competitive performance without the need for learned image tokenizers. In this work, we study whe
- PaperIn Human Memories. Technology, Creativity and Self-Determination: An Ethical Proposal
This research investigates the role of artificial intelligence (AI) in modern compositional practices, with a particular focus on two case studies: Convergence (2020/21)
- PaperJAXtari: High-Throughput and Easy-to-Modify Arcade Learning Environment
The Arcade Learning Environment (ALE) has been a cornerstone of Deep Reinforcement Learning research, providing a standardized benchmark for evaluating general agents. Ho
- PaperScalable long-range machine learning interatomic potentials with electrical response for atomistic material modeling
Accurate atomistic simulations of materials under electric fields require long-range electrostatics and electrical-response modeling at length scales beyond the reach of
- PaperDiversity Without Labels: Task-Agnostic Coreset Selection Across Perception and Action
While data collection for model training is relatively easy, curating high-quality datasets from large collections is inherently challenging. Coreset estimation methods a
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.