Search: “model-releases”

Serverless gossip training of LSTM failure detectors: A matched-protocol comparison with federated, local and centralized learning on NASA C-MAPSS

arXiv:2609.35792v1 Announce Type: new Abstract: Industrial predictive maintenance increasingly depends on learning from equipment spread across sites whose sensor data cannot easily be pooled. Federat

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Simple Agentic Memory for Generalist Robot Policies

arXiv:2609.36595v1 Announce Type: cross Abstract: Visual-memory systems commonly retain or compress past observations. Robot control additionally requires interaction-derived state that no individual

SINGED: Correct Outputs Do Not Certify Safe Execution in LLM Agents

arXiv:2609.35889v1 Announce Type: cross Abstract: Tool-using language-model agents select and execute third-party artifacts. Different implementations can return the requested output while producing h

SINO: Scale-Invariant Neural Operator

arXiv:2609.36890v1 Announce Type: new Abstract: In scientific machine learning, physical fields governed by partial differential equations exhibit low-rank structure and scale invariance. When solving

SoL-Refiner: Speed-of-Light One-Step Refinement for High-Resolution Video

arXiv:2609.37969v1 Announce Type: new Abstract: High-resolution video generation is expensive, as its cost grows rapidly with the number of spatiotemporal tokens. A practical alternative first generat

Spatial-OPSD: Self-Improving Spatial Reasoning via Label-Free Self-Distillation

arXiv:2609.37055v1 Announce Type: new Abstract: Vision-language models (VLMs) increasingly operate in embodied and spatially grounded settings, where accurate understanding of depth, viewpoint, and th

SPLASH: Switching Parallel Layouts of Attention with Seamless Handoff for LLM Serving

arXiv:2609.37626v1 Announce Type: cross Abstract: No single way of parallelizing attention serves large language models well under all loads. Low concurrency favors tensor parallelism, many independen

Spotter: Let the Embodied Model Lead, and the VLM Reflect for It

arXiv:2609.36808v1 Announce Type: cross Abstract: Current embodied models do not respond to their own failures, although what just went wrong could inform a small adjustment on the next attempt, the k

SQUARE: Structured Quantum Representation Adapters as Compact Quadratic Feature Maps for Frozen Language Models

arXiv:2609.37134v1 Announce Type: cross Abstract: Frozen language models (LMs) are increasingly used as fixed feature extractors for downstream reranking, scoring, and preference modeling, raising a p

SRJudge: Empowering Large Language Models with Selective Reasoning for Fine-Grained Knowledge Concept Tagging

arXiv:2609.36982v1 Announce Type: cross Abstract: Knowledge concept tagging aims to assign specific concept or topic labels to educational content, which is essential for both educators and learners i

State Transport Routing for Short-horizon Adaptation in Multi-horizon Photovoltaic Forecasting

arXiv:2609.36926v1 Announce Type: cross Abstract: Recent power measurements provide valuable information for photovoltaic(PV) power forecasting, but directly extrapolating short-term trends can introd

StateTape: Action-Conditioned Evidence Lifecycle Modeling for Long-Horizon Coding Agents

arXiv:2609.36319v1 Announce Type: new Abstract: Despite the recent success of coding agents built on large language models, it remains challenging to run them over long horizons, since every observati

Stochastic Heavy Ball with Polyak Step Size and Armijo Line Search: A General Convergence Analysis

arXiv:2609.36668v1 Announce Type: new Abstract: Polyak step size (PS) and Armijo line search (ALS) have received increasing attention in stochastic optimization, with encouraging empirical performance

Stochastic World Models for Verifying Vision-Based Neural Feedback Systems

arXiv:2609.38120v1 Announce Type: new Abstract: Verifying a vision-based neural feedback system requires a model of the observations its controller acts upon. Such a model must capture the variation t

Storage Is Not Strategy: State-Conditioned Support Control for LLM Unlearning

arXiv:2609.37858v1 Announce Type: cross Abstract: Many localized large language model (LLM) unlearning methods select a small parameter subset from a localization signal and keep it fixed during optim

Suppression Is Not Forgetting: Residual Recoverability in Visual Concept Unlearning for VLMs

arXiv:2604.03114v2 Announce Type: replace-cross Abstract: Vision-language models (VLMs) may need to forget visual concepts after deployment because of privacy, copyright, licensing, safety, or policy

Systematic Multi-Agent Vision-and-Language Navigation: Formulation, Benchmark, and Method

arXiv:2609.35965v1 Announce Type: cross Abstract: Vision-and-Language Navigation (VLN) has largely focused on a single agent following a single instruction, yet many real-world applications require te

T^2Mem: Learning Test-Time Memory for Robotics

model-releasesarxiv-cs-ro

arXiv:2609.36720v1 Announce Type: new Abstract: Memory-dependent robotic manipulation requires policies to use information that is no longer available in the current observation. Retaining history alo

TabFM: A Zero-Shot Foundation Model for Tabular Data

arXiv:2609.37959v1 Announce Type: new Abstract: Tabular machine learning typically relies on per-dataset workflows, fitting tree ensembles or running AutoML searches from scratch for every task. We pr

TabFM-Auto: Self-Evolving Pipelines for Tabular Foundation Models

arXiv:2609.37989v1 Announce Type: new Abstract: Tabular foundation models achieve strong zero-shot accuracy on structured data by pretraining on synthetic tables, but they ignore the column names, tas

TabKD: Tabular Knowledge Distillation through Interaction Diversity of Learned Feature Bins

arXiv:2603.15481v3 Announce Type: replace-cross Abstract: Data-free knowledge distillation enables model compression without original training data, critical for privacy-sensitive tabular domains. How

TagPR: Tag-Guided Process Supervision for Personalization Reasoning in Large Language Models

arXiv:2509.23140v2 Announce Type: replace Abstract: Recent advancements have endowed Large Language Models with impressive general reasoning capabilities. However, these reasoning models often perform

Taming VLAs under Robot Execution Errors: Self-Compensation and Stress Testing

model-releasesarxiv-cs-ro

arXiv:2609.37334v1 Announce Type: new Abstract: Vision-language-action (VLA) policies often fail when a robot's executed motion deviates from their commanded action. Such execution errors arise from t

Teaching LLMs to Generate Challenging MILP Instances via Solver Feedback

arXiv:2609.37356v1 Announce Type: new Abstract: Generating optimization instances that are both feasible and computationally challenging is crucial for benchmarking solvers and training learning-based

Tensor-Train Compressed Separable PINNs: A Curvature-Aware Optimization Framework for Parametric PDEs in High Dimensions

arXiv:2609.36165v1 Announce Type: cross Abstract: In this work, we develop a second-order optimization framework for physics-informed neural networks (PINNs) applied to high-dimensional parametric par

The Camera Inside the Editor: Reading the Implicit Camera of Image Editors with Painted Calibration Patterns

arXiv:2609.37732v1 Announce Type: new Abstract: Instruction-based image editors insert objects, restyle scenes and render new viewpoints, but it is unknown which camera they assume when they paint int

The Decision Value of Perception Compute

arXiv:2609.35910v1 Announce Type: cross Abstract: Adaptive perception spends extra computation on inputs where perception is expected to improve. When perception feeds a downstream decision system, a

The Domain Is a Residue: Adapting Self-Supervised Features, Not Generators

arXiv:2609.37330v1 Announce Type: new Abstract: Clearing fog, rain or snow from footage, or turning renders into photographs, must remove the source domain and keep the scene. Unpaired translators car

The Unequal Influence of Bad Advice: Using Training Data Attribution to Modulate Emergent Misalignment

arXiv:2609.37914v1 Announce Type: cross Abstract: Fine-tuning large language models on narrow, misaligned tasks can undo their post-training alignment and induce novel misaligned behaviors -- a phenom

Think, Then Look: Active Spatial Reasoning for House-Scale 3D Scene Understanding

arXiv:2512.03284v2 Announce Type: replace Abstract: Spatial reasoning in large-scale 3D environments remains challenging for current vision--language models, which are typically constrained to room-sc

Thinking Before Thinking: Scaling Agentic Inference Through Meta-Reasoning

arXiv:2609.38147v1 Announce Type: new Abstract: As agents take on longer and more complex problems, controlling the execution becomes a task in its own right. Each step in the run brings new control c

ThinQuant: Scalable Rotation Learning for Weight and Activation Quantization of LLMs

arXiv:2609.36120v1 Announce Type: cross Abstract: Learned rotations play an important role in enabling low-bit weight and activation quantization of large language models by smoothing outliers in the

TomoTransformer: Towards a Foundation Model for CT Reconstruction

arXiv:2609.37605v1 Announce Type: new Abstract: Supervised deep learning has advanced sparse-view tomographic reconstruction. However, conventional models, which typically map filtered back-projection

TORQUE: Optimizing What (not) to Quantize Before and After Rotation

arXiv:2609.36032v1 Announce Type: cross Abstract: Uniform random rotations are an effective preprocessing step for quantization: they make normalized coordinate distributions approximately Gaussian, e

TRACE: Deployable Tree-Relational Structure Enhancement for Oncology LLMs

arXiv:2609.35810v1 Announce Type: cross Abstract: Large language models are increasingly used in oncology applications, but their predictions are often weakly grounded in explicit medical structure. W

Trajectory Soup: Pushing the Compute-Scaling Frontier of LLM Mid-training via Diverse Trajectories

arXiv:2609.37169v1 Announce Type: cross Abstract: Mid-training equips pretrained large language models with specialized and reasoning capabilities, but the returns of this stage are bounded since addi

Transolver-sigma: Joint Spectral-Physical Subspace Modeling for Neural PDE Solving

arXiv:2609.37279v1 Announce Type: new Abstract: Neural solvers offer efficient surrogates for numerical simulation of partial differential equations (PDEs). For time-dependent problems, strong one-ste

Triadic Linear Attention: Three-Dimensional Recurrent States for Long-Context Sequence Modeling

arXiv:2609.36529v1 Announce Type: cross Abstract: Recurrent neural networks (RNNs) compress the historical context into a memory state of fixed size, thus allowing for constant-time inference. The mem

UltRAG: a Universal Simple Scalable Recipe for Knowledge Graph RAG

arXiv:2603.28773v2 Announce Type: replace-cross Abstract: Large language models (LLMs) frequently generate confident yet factually incorrect content when used for language generation (a phenomenon oft

Understanding LLM Parameter Update Sparsity through the Lens of Fisher

arXiv:2609.36262v1 Announce Type: new Abstract: Recent studies have observed that parameter changes during language-model post-training can be concentrated in a small subset of coordinates. This pheno

UniBuild: Unified Building Mapping From Multi-Source Optical Remote Sensing Imagery With Detail Decoding and Geometry Regularization

arXiv:2609.37031v1 Announce Type: new Abstract: Building extraction from optical remote sensing (RS) imagery is fundamental to urban mapping, yet existing methods are often dataset-specific and genera

UnlearningSoup: Is Repeated Tuning Necessary for Large Language Model Unlearning?

arXiv:2609.37076v1 Announce Type: new Abstract: Large language models trained on vast corpora inherently risk memorizing harmful content that may later re-emerge in their outputs. To mitigate this iss

UserProxyBench: Evaluating LLM User Simulators for Agent Benchmarks and Training

arXiv:2609.38043v1 Announce Type: new Abstract: Interactive agent benchmarks and multi-turn reinforcement learning increasingly place a second language model in the role of the user. This simulated us

VehicleArena: A Realistic Urban Environment for Multi-Agent Driving

arXiv:2609.35916v1 Announce Type: cross Abstract: Real-world embodied agents often pursue independent objectives within a shared physical environment, where their actions can alter the conditions face

VeriWeave Govern: Evidence-Gated Deterministic Runtime Governance for Enterprise AI Agents

arXiv:2609.37457v1 Announce Type: new Abstract: Enterprise artificial-intelligence agents increasingly call tools, modify infrastructure, and process protected data, creating a need to separate action

VesselBench-800K: A Large-scale Perception Benchmark for Multimodal Vessel Detection, Counting, and Density Estimation

arXiv:2609.37003v1 Announce Type: new Abstract: Vessel perception from space is crucial for a wide range of maritime applications, from traffic monitoring to environmental protection. However, most ex

Video2Skill: From Streaming Experience to Reusable Embodied Skills

arXiv:2609.36691v1 Announce Type: new Abstract: Manipulation behaviors vary widely across objects and scenes, but they share a small set of reusable skills, and planning with these skills helps embodi

Video2STL: Grounding VLM-Generated Temporal Specifications for Robot Learning

arXiv:2609.37519v1 Announce Type: cross Abstract: Video-based policy learning is particularly promising, as it illustrates target behaviors without requiring action annotations or embodiment-matched d