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Everything new in AI as it appears: launches announced by the labs, brand-new models, datasets, papers and open-source tools. Checked every minute or two. Launches feed · Trending · News
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Saturday 17 October
- PaperAre We Evaluating VLM Token Pruning Right? Looking Beyond Accuracy and Token Count
Visual token pruning aims to reduce inference cost while preserving the capabilities of the original VLM. Yet existing evaluations rely on aggregate task accuracy and ret
- PaperToward Collective Model Intelligence: Characterizing and Coordinating Models
Independently developed AI models accumulate diverse and complementary capabilities, but a growing model collection does not automatically realize Collective AI. Addressi
- PaperEditing Images into Reusable Layers via Compositional Edit-Prior Distillation
High-quality image editing requires precise modification of target regions while preserving the content of unrelated regions. Existing editing models produce flattened ou
- PaperGaussian Process Bandits with Paired Auxiliary Observations
Bayesian optimization (BO) is widely used for expensive black-box optimization, yet observation noise makes each evaluation less informative and slows posterior learning.
- PaperHow Does Muon Work in Private Deep Learning? Scalable Differentially Private Training via Orthogonalization
Training deep neural networks requires optimizers that balance computational efficiency with formal data privacy. While orthogonalized update rules, such as the recently
- PaperCan LLM Agents Resolve Service Failures? Simulating Multi-Turn Complaint Handling under Information Asymmetry
LLM agents are widely adopted in service chatbots for rule-guided support and information access, yet emotionally demanding complaint handling still relies heavily on hum
- PaperGLOSS-MT: Controllable Low-Resource Machine Translation with an Editable Dictionary
Adapting a pretrained machine translation (MT) model to new terminology usually requires new parallel data and another round of fine-tuning, which is costly for low-resou
- PaperfxBench: Evaluating and Understanding Formula Suggestions in Spreadsheets
Spreadsheets are among the most widely used tools for computations, and formulas are their core building blocks. Besides agentic spreadsheet tools, proactive formula sugg
- PaperShlokaDhara: A Multi-Speaker Sanskrit Speech Corpus for Learning Meter-Aware Prosody in Text-to-Recitation
Sanskrit verse recitation is governed by $\textit{Chandas}$, a strict prosodic framework defined by rhythmic $\textit{Laghu}$ (light) and $\textit{Guru}$ (heavy) syllable
- PaperWhere Natural Language Ends in Agents: Executable Skill Composition with MetaSkill
Agent Skills express open-ended task knowledge in natural language, but composing them requires persistent execution order and upstream-output handoffs. We propose select
- PaperPV-Decoding: Progressive Verification Decoding with Decode Gating for Diffusion Language Models
Discrete diffusion language models (dLLMs) offer an attractive alternative to autoregressive generation by updating multiple tokens in parallel, but their inference effic
- PaperTensor Network Datamodels for Training Data Attribution
Datamodels predict how a model's behavior changes when different parts of its training data are included or removed. However, linear datamodels assign fixed contributions
- PaperNeuro-Inspired Inhibitory Message Passing for Accurate and Token-Efficient Multi-Agent Reasoning
Multi-agent systems promise to solve problems by bringing together information beyond the reach of any individual agent. Retrieval and tool use can distribute this inform
- PaperDiffuPlan: Editable Planning State for Diffusion Language Model Agents
Diffusion language models (dLLMs) are emerging as an alternative to autoregressive (AR) language models, yet dLLM agents largely inherit an interaction protocol designed
- PaperWhen Do Repetition Loops Lock? Truncation Sampling, Bounded Penalties, and a Blind Spot in DRY
Language models sometimes repeat verbatim until the generation limit. We study the exit rather than the entrance: given that a span has already been repeated $n$ times, w
- PaperMultilingual Brain Decoding Reveals Shared Cortical Semantic Geometry
Human languages differ markedly in lexical and syntactic form yet can convey similar semantic content. The neural basis of this cross-language semantic commonality remain
- PaperSQuIREL: A Context-Relative Framework for Measuring Entity Richness in Wikidata
Wikidata is a large, heterogeneous knowledge graph and applying data quality metrics requires context-specific approaches. The "richness" quality metric is currently unde
- PaperSpherical Physics-informed Neural Operator with Multi-scale Coupling for Meteorological Downscaling
Meteorological downscaling is crucial for high-resolution regional climate forecasting and disaster early warning. While neural operators have emerged as a promising para
- PaperAtomSD: Procedural Atom-Guided Self-Distillation for LLM Agents
Large language models (LLMs) possess broad factual knowledge and strong reasoning capabilities, but solving complex tasks also requires procedural knowledge about how to
- PaperSuperClip Pyramid for Video Temporal Grounding
With the rapid expansion of online video content, video temporal grounding has become essential for localizing moments based on user-specific queries, comprising two subt
- PaperNative Probability Outputs for Clinical Triage: An Evaluation of Calibration and Decision Accuracy
Patient-facing triage requires an appropriate care recommendation and recognition of when information is insufficient. We evaluate whether Jev, a decision model that retu
- PaperVerifying Human-Written Reasoning References
Evaluating the reasoning of AI systems often relies on human-written reasoning chains as references, yet the logical support for their individual steps is rarely verified
- PaperGeometry-Aware Interpolation for Inverse Problems
Recovering missing visual information from incomplete or degraded images remains a challenging problem, particularly when spatial variations and complex image structures
- PaperContrastive Adversarial Training for Robust Graph Neural Networks under Label Poisoning
Graph Neural Networks (GNNs) are effective for modeling relational data but are vulnerable to label poisoning, where a small number of corrupted training labels can propa
- PaperMM-LeJEPA: Correlated Gaussian Regularization for Multimodal Joint-Embedding Predictive Architectures
LeJEPA derives an isotropic Gaussian embedding target by minimizing, under its task assumptions, a Fisher information criterion that controls the task-averaged squared pr
- PaperMESS: Multi-Exposure Sequence Synthesis for Generalizable Image Enhancement
Despite the significant progress in image enhancement under adverse illuminations, such as low-light image enhancement, exposure correction, and backlit image enhancement
- PaperFrom Views to Worlds: Active Exploration over 3D Worlds for Vision-Language Models
Vision-language models (VLMs) have achieved remarkable progress in 2D visual understanding tasks, yet the passive view-centric perception paradigm limits their capacity f
- PaperDataPraxis: Scaling Analytics Tasks via Verified Workspace Evolution
General-purpose agents are increasingly expected to perform professional analytics work, which requires sustained reasoning, iterative investigation, and reliable evidenc
- PaperDo Conversational Agents Need Explicit Memory? A Controlled Comparison with Raw-History Retrieval
Explicit memory systems transform conversation history into persistent representations intended to improve future access, often at substantial construction cost. Yet it r
- PaperKnowledge Diversion: A Novel Paradigm for Pre-training Decomposable Image Generation Models
Large-scale pre-trained models have become foundational to modern machine learning, yet conventional pre-training objectives primarily optimize source-domain performance
- PaperWhat RL Brings to Reasoning: A Few Decisions the Base Model Would Not Make
Reinforcement learning with verifiable rewards (RLVR) substantially improves mathematical reasoning, but what it adds to the base model remains unclear. We investigate th
- PaperFrom Prediction to Action: Population Health World Model for Digital Medicine
Digital medicine now captures data that traces individual health trajectories and reveals population health dynamics through electronic health records, claims, remote mon
- PaperCan AI agents make law? Evaluating AI legal relevance and creativity
Large language models, the artificial intelligence (AI) systems behind modern chatbots, are trained on vast amounts of legal text, but can they build on it to write law f
- PaperLightweight Machine Learning for Classifying Disaster-Related Social Media Posts
Classifying disaster-related social-media posts into humanitarian information labels is challenging because individual messages are typically short and context-limited, h
- PaperGood Judgment, Bad Advice: Decision-Model Controllers Raise Agent Cost Without Improving Success
Agent scaffolds increasingly delegate small decisions (whether to stop, verify, or change approach) to cheaper models. We ask whether a typed decision model, Jev 1.13, co
- PaperCaMeWM: A Causal Medical World Model for Generative Tumor Evolution and Treatment Planning
Treatment planning is intrinsically counterfactual: clinicians must compare how a patient's tumor and survival would evolve under competing regimens, whereas a retrospect
- PaperEdgeKernelBench: Unified LLM-Driven Kernel Generation for Edge Backends
Recent works show that LLMs can generate kernels with strong performance on server GPUs. Edge deployment presents distinct challenges because the hardware is heterogeneou
- PaperModeling Uncertainty Propagation in 3D Morphable Models
We study the problem of mapping parameter-space variance of a 3D Morphable Model (3DMM) to per-vertex variance. Traditionally, per-vertex variance has been used to visual
- PaperFrequency-Domain Membership Inference Does Not Beat Confidence Thresholding: A Band-Resolved Analysis of Why
A widely repeated account of membership inference holds that models lean on fine-grained detail for samples they have memorized, so degrading an input's resolution should
- PaperSpectral-Aware Proposal Enhancement for Diffusion-Based Multispectral UAV Multi-Object Tracking
Multispectral UAV multi-object tracking (MOT) with oriented bounding boxes remains challenging due to small targets, cluttered backgrounds, and unstable inter-frame assoc
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.