Search: “model-releases”

What Do Tabular Foundation Models Compute In Context? In-Situ Representation Refinement through Attention-Gated Updates

arXiv:2609.27679v1 Announce Type: new Abstract: What reusable computation should a tabular foundation model learn when every table defines a new supervised task? We develop in-situ representation refi

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Model Releases

What Looks Like a Capability Limit in Vision-Language Models Is a Readout Limit

DGX agent

arXiv:2609.27408v1 Announce Type: cross Abstract: Benchmarks for vision-language models offer their answer choices in some convention: a letter, a color name, a pixel coordinate. That convention is tr

model-releasesarxiv-cs-ai

24 Sept 2026

When Adaptation Hurts: Split Sensitivity and Person-Level Negative Transfer in Federated Wearable Onboarding

arXiv:2609.27819v1 Announce Type: new Abstract: Federated wearable models eventually serve people absent from source training, but favorable average accuracy does not establish that unlabeled onboardi

When Clients Are Orchestrated: Strategic Gradient Manipulation to Defeat Federated Learning Servers with Efficient Defense

arXiv:2609.27124v1 Announce Type: cross Abstract: Federated Learning enables decentralized model training by exchanging model updates--rather than raw data--with a central parameter server (PS). While

When Context Misleads: In-context Learning with Jurisdiction in Large Language Models

arXiv:2609.27603v1 Announce Type: cross Abstract: In-Context Learning (ICL) has become a cornerstone of modern LLM deployment. However, existing ICL post-training methods have a critical blind spot: t

When Labels Are Scarce: An Oscillatory State Space Model for Vibration Diagnosis

arXiv:2609.27411v1 Announce Type: new Abstract: Machine fault diagnosis from vibration requires learning from scarce labelled fault recordings while meeting the computational constraints of edge devic

When Post-Processing Fairness Constraints Help and When They Harm: Evidence from Eight Cross-Domain Evaluations

arXiv:2609.26955v1 Announce Type: new Abstract: Fairness audits in production ML typically occur once, at deployment, on a single domain. Both fail in practice: fairness can shift after retraining or

X2Real: an eXtensive simulation benchmark for real-world generalist policies

arXiv:2609.27449v1 Announce Type: new Abstract: Generalist robot manipulation policies have developed rapidly, yet their reliable evaluation remains challenging due to fundamental flaws in existing si

XLOG: A CUDA-Native Engine for Neurosymbolic Integration

arXiv:2609.27203v1 Announce Type: new Abstract: xlog is a CUDA-native logic programming engine integrating neural perception with deterministic Datalog, probabilistic inference, and epistemic world vi

ZO-COSMO: Index-Free One-Hop Mixing for Decentralized Zeroth-Order Optimization

arXiv:2609.27199v1 Announce Type: new Abstract: Sparse communication in decentralized zeroth-order learning requires compatible peer-state coordinates. We characterize this one-hop condition and devel

A Deployment Study of Identity-Gated Drone Gesture Control

arXiv:2609.25511v1 Announce Type: new Abstract: Vision-based gesture control accepts commands from any hand in the camera field of view, which is unsafe in shared indoor spaces. This paper presents IG

A Governance-Aware Large Language Model Orchestrated Agentic Digital Twin for Transmission System Operator Control Room Decision Support

arXiv:2609.22476v1 Announce Type: cross Abstract: Transmission system operators face rising complexity from renewable integration, reduced inertia, and tighter security margins. Large language models

A JEPA Recipe for Tabular Foundation Models

arXiv:2609.25541v1 Announce Type: new Abstract: Tabular foundation models learn to predict cell values in context, whereas world-model self-supervision asks for prediction in representation space (LeC

A Lightweight Plastic-Memory Framework for Graph Few-Shot Class-Incremental Learning

arXiv:2609.25781v1 Announce Type: new Abstract: Graph Incremental Learning has garnered increasing attention as dynamic graph data continues to emerge across diverse fields. Conventional approaches pr

A Multimodal Large Language Model-Driven Framework for Context-Aware UAV Emergency Landing Site Selection

arXiv:2602.01163v2 Announce Type: replace Abstract: Safe UAV emergency landing requires more than just identifying flat terrain; it demands understanding complex semantic risks (e.g., crowds, temporar

Activation-Energy Pruning for Spiking Neural Networks: Unsupervised Personalization via Spike-Count Saliency

arXiv:2609.26167v1 Announce Type: new Abstract: Activation-energy pruning -- removing weights whose product of magnitude and cumulative pre-synaptic spike count falls below a threshold -- was establis

Agensh: Scaling Organizational Intelligence to 1,024 Agents

arXiv:2609.26781v1 Announce Type: new Abstract: A multi-agent system can reduce latency on complex tasks by executing work concurrently. Several pioneering harness frameworks support multi-agent syste

AgentBetta: Verification-Driven Adaptive Configuration of an AI Nano-Agent through Selective Expansion and Verified Contraction

arXiv:2609.23512v1 Announce Type: new Abstract: Large language model agents are typically deployed with predefined configurations, although the required model capability, context, tools, permissions,

AIBuildAI-2.5: Efficient Autonomous AI Model Development Through LLM-Guided Tree Search

arXiv:2609.25047v1 Announce Type: new Abstract: Autonomous agents that automatically build artificial intelligence (AI) models could broaden access to AI across science and engineering. A popular line

An Action Is Worth One Patch: Unified World-Action Modeling with PatchWAM

arXiv:2609.25961v1 Announce Type: new Abstract: Generative visual models offer a foundation for learning representations of physical dynamics, yet their extension to continuous control raises a fundam

An Exploratory Replica-Overlap Probe of the Grokking Transition

arXiv:2609.25634v1 Announce Type: new Abstract: We trained 64 independently seeded networks in four configurations, continuing each to sustained convergence or a 40,000-epoch ceiling. We then asked wh

Annual Earth-observation embeddings encode wildfire disturbance and support simplified burned area mapping

arXiv:2609.25731v1 Announce Type: new Abstract: Medium-resolution (10-30 m) burned area mapping is vital for monitoring wildfires and their impacts, but remains difficult to scale. Existing methods re

APEXA: Execution-Integrity Enforcement for Multi-Agent LLM Automation of Synchrotron Data Reduction

arXiv:2609.24165v1 Announce Type: new Abstract: Synchrotron data reduction, detector calibration followed by azimuthal integration of terabyte-scale diffraction series, is a multi-step, expert-bound b

Auditing Proxy-Based Validation Across Text Spans

arXiv:2609.25808v1 Announce Type: cross Abstract: Evaluation scores are often validated by their agreement with inexpensive proxy labels. When the score and the proxy are computed from the same text s

AURA: Angular Update Rate Adaptation for training complex-valued neural networks

arXiv:2609.25914v1 Announce Type: new Abstract: Complex-valued neural networks (CVNNs) are increasingly adopted for complex-valued data; however, they are often trained with first-order optimizers inh

Automatic depth-based local center clustering via eta-integrated local depth and adaptive grouping

arXiv:2609.26748v1 Announce Type: cross Abstract: Clustering is an unsupervised learning technique that partitions unlabeled data into groups. Most existing methods require user-specified parameters,

BackTrend: Evaluating Scientific Weak-Signal Prediction via Backward Reconstruction

arXiv:2609.24921v1 Announce Type: new Abstract: Scientific weak signals are early, low-visibility research directions that later become central to mature scientific topics, yet existing resources such

BananaVLM: A Domain-Adapted Vision Language Model for Banana Crop Disease Diagnosis

arXiv:2609.25040v1 Announce Type: cross Abstract: Banana crop diseases threaten food security across the world, yet field diagnosis remains difficult because of limited expert access and visual simila

Bayesian Fusion of Active Contour Models and ConvNet Priors for Standing Dead Tree Segmentation

arXiv:2410.07421v2 Announce Type: replace Abstract: Instance segmentation is a core computer vision task with great practical significance. Recent advances, driven by large-scale benchmark datasets, h

Beyond Endpoint Performance: Process-Level Evaluation of Self-Evolving Agents

arXiv:2609.24663v1 Announce Type: new Abstract: Self-evolving agents convert interaction feedback into persistent artifacts, such as memories or skills, which in turn guide subsequent decisions. As th

Beyond Short Segments : Expanding Speaker Embeddings with Vector Archives

arXiv:2609.25007v1 Announce Type: cross Abstract: The performance of state-of-the-art speaker verification (SV) systems severely degrades on short utterances due to insufficient speaker-specific infor

Beyond Static Charts: Can Language and Vision Language Models Generate Interactive Data Visualization Interfaces?

arXiv:2609.26208v1 Announce Type: new Abstract: Data visualization is central to analytical reasoning, but real-world analysis increasingly requires language-driven interactive interfaces rather than

BigO(Bench): Can LLMs Generate Code with Controlled Time and Space Complexity?

arXiv:2503.15242v3 Announce Type: replace Abstract: We introduce BigO(Bench), a novel coding benchmark designed to evaluate the capabilities of generative language models in understanding and generati

Block-Level Weight-Space Structure Persists Under Post-Training: An Empirical Study Across LLM Families

arXiv:2609.26147v1 Announce Type: new Abstract: Modern LLMs are deployed as families of post-trained variants (base, instruct, chat, code) derived from a shared set of pre-trained weights. We present

Building Trustworthy Mental Health Benchmarks on Bluesky: A Validation-Aware Weak-Supervision Framework

arXiv:2609.22696v1 Announce Type: new Abstract: Decentralized social media platforms create new opportunities and challenges for computational mental health research because data access, moderation, l

C2FXNet: Coarse-to-Fine Scene Expert for Unified Object Detection across Adverse Weather

arXiv:2609.25693v1 Announce Type: new Abstract: Object detection in adverse weather remains challenging because severe degradations weaken visual quality and disrupt semantic feature representations a

CableVLA: Simulation-Privileged Global-Local Representation Learning for Cable Routing

arXiv:2609.25606v1 Announce Type: new Abstract: Cable routing requires coordinated control of global cable topology and changing local contacts. We present CableVLA, an end-to-end multimodal vision-la

CacheDyG: Decoupling Temporal Propagation for Efficient Dynamic Graph Learning

arXiv:2609.25814v1 Announce Type: new Abstract: Dynamic graphs are widely used to model time-evolving relational systems in real-world applications. Dynamic graph neural networks provide an effective

Calibration Count Reuse: Validity Does Not Determine Efficiency

arXiv:2609.25138v1 Announce Type: cross Abstract: Calibration count reuse raises separate validity and efficiency questions. We give a validity criterion for general count-dependent nonconformity scor

Can You Delete a Year of Market Data? Machine Unlearning Against Exact Retraining Oracles

arXiv:2609.26242v1 Announce Type: new Abstract: When a data license expires, deleting stored records does not remove influence encoded in a trained forecaster. Machine unlearning seeks to remove this

Capable yet Parsimonious: Extracting and Characterizing Hidden Chain-of-Thought in Frontier Models

arXiv:2609.26637v1 Announce Type: new Abstract: The rapid capability gains of frontier language models are widely attributed to improved reasoning abilities, yet this cannot be verified as raw CoT tra

Certified Against Which Oracle? Execution Labels Set the Reported Risk of Conformal Abstention for Text-to-SQL

arXiv:2609.25938v1 Announce Type: cross Abstract: A conformal abstention certificate for text-to-SQL is only as truthful as the correctness labels it is calibrated on. The uncertainty pipelines that r

ChainDoRA: Tensor-Train Factorized Weight-Decomposed Low-Rank Adaptation for Parameter-Efficient LLM Fine-Tuning

arXiv:2609.25058v1 Announce Type: new Abstract: Parameter-efficient fine-tuning (PEFT) adapts large language models (LLMs) to downstream tasks while updating only a small fraction of their pretrained

ChemVTS-Bench: Evaluating Visual-Textual-Symbolic Reasoning of Multimodal Large Language Models in Chemistry

arXiv:2511.17909v2 Announce Type: replace Abstract: Chemical reasoning inherently integrates visual, textual, and symbolic modalities, yet existing benchmarks rarely capture this complexity, often rel

CivBench: Progress-Based Evaluation for LLMs' Strategic Decision-Making in Civilization V

arXiv:2604.07733v2 Announce Type: replace Abstract: Evaluating strategic decision-making in LLM-based agents requires generative, competitive, and longitudinal environments, yet few benchmarks provide

CliffCompaction: Cost-Efficient Compaction for Long-Horizon Coding Agents

arXiv:2609.26779v1 Announce Type: cross Abstract: Agents often work on complex problems that require millions of tokens of context, which necessitates compacting across sessions due to limited context

Combinatorial Network-Based Manifold Topological Deep Learning for Image Analysis

arXiv:2609.25453v1 Announce Type: new Abstract: Medical image analysis remains fundamentally challenging because of the intricate geometric and topological structures present in medical data. Conventi

Combining Hierarchical Cognitive Process with Process Supervision for Interpretable Scene Safety Understanding

arXiv:2609.26399v1 Announce Type: new Abstract: Scene safety understanding plays a life-or-death role in situational awareness in various critical domains. Traditional methods that rely on learning di