Search: “models”

Mitigating Exploration Bias in RL for Multi-Instruction Following

arXiv:2608.23830v1 Announce Type: cross Abstract: RL has emerged as a powerful paradigm for enhancing the instruction following capabilities of LLMs. While existing training recipes achieve substantia

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Multi-Stage Prompt-Guided Feature Modulation for Generalizable Brain Tumor Segmentation

DGX agent

arXiv:2608.23745v1 Announce Type: cross Abstract: Accurate brain tumor segmentation from magnetic resonance imaging (MRI) is essential for diagnosis, treatment planning, surgical guidance, and disease

researcharxiv-cs-cv

26 Aug 2026

NeurRAFT: Robot Motion Planning via Anchor-Level Flow Matching with Clearance-Aware Preference Tuning

arXiv:2608.24026v1 Announce Type: new Abstract: Recent end-to-end neural motion planners generate trajectories from raw sensor observations, avoiding the privileged geometric models required by classi

local-aiarxiv-cs-ro

NVIDIA Cosmos-H-Dreams: Real-Time Generative Physics Simulation for Surgical Robotics

arXiv:2608.24199v1 Announce Type: new Abstract: Generative simulation for surgical robotics still lacks real-time interaction. Physical-robot experiments, often involving animal or cadaver labs, are t

safetyarxiv-cs-ro

Observability Engineering: From Measurement to Information Generation in Active Sensing Systems

arXiv:2602.13554v2 Announce Type: replace-cross Abstract: This article develops a four stage observability engineering framework for interaction driven sensing. The framework integrates physical model

researcharxiv-cs-ro

Parameter-Level Attribution of Symmetry in Trained Networks Though Parameter-Wise Functional Sensitivity

arXiv:2608.24700v1 Announce Type: new Abstract: When a network has learned a function with a known symmetry, can that symmetry be moved through the parametrisation---is there a motion in parameter spa

Parameterized Complexity of L_p-Lipschitz Constants for Input Convex Neural Networks and L_p-Norm Maximization over Zonotopes

arXiv:2608.24865v1 Announce Type: cross Abstract: Lipschitz constants are a standard way to quantify the sensitivity of neural networks to small input perturbations, but computing them is difficult ev

PeakBench: Benchmarking Resource-Aware Tool Invocation in LLM Agents

arXiv:2608.24509v1 Announce Type: new Abstract: LLM agents increasingly solve tasks by invoking multiple tools, where parallel execution is essential for low latency but difficult to manage safely. Ex

Physics-Integrated Operator Learning via Gaussian Splatting Representations

arXiv:2608.24049v1 Announce Type: new Abstract: Neural operators provide efficient surrogates for spatiotemporal PDE systems, but purely data-driven formulations often accumulate substantial errors du

PhysMLLMs: Spatial Priors for Unified Referring Segmentation and Grounded Reasoning of Images and Videos

arXiv:2608.24574v1 Announce Type: new Abstract: Video multimodal large language models support language guided video segmentation, but they often show spatio temporal inconsistencies, e.g., jitter, dr

safetyarxiv-cs-ai

Pivot-and-Station Multi-Agent Path Finding: Solvability, Complexity, and Algorithms

arXiv:2608.24585v1 Announce Type: new Abstract: Automated high-density storage systems (warehouses, robotic parking, plant logistics, etc.) require fleets of agents to move through scarce task-critica

Predictability of El Nino from Delayed Observations

arXiv:2608.24428v1 Announce Type: cross Abstract: Using monthly Nino-3.4 anomalies through July 2026, we investigate how much predictive information is contained in delayed observations of the index.

researcharxiv-cs-lg

Provenance Guided Incremental Learning Under Evolving Concept Definitions

arXiv:2608.23893v1 Announce Type: new Abstract: Learning systems deployed over long periods must adapt not only to statistical changes in incoming data, but also to revisions of the definitions that g

qshap: Fast Shapley Decomposition of R^2 for Gradient-Boosted Trees

arXiv:2608.24104v1 Announce Type: cross Abstract: Numerous methods have been developed to quantify feature attributions in individual predictions for tree ensembles. However, many applications require

local-aiarxiv-cs-lg

Applications

Replicable Conformal Prediction

arXiv:2608.23638v1 Announce Type: cross Abstract: Two analysts who calibrate the same predictive model on independent samples will deploy different prediction sets every time, because the calibration

applicationsarxiv-cs-lg

ReproAgent: Contract-Guided Paper-to-Code Reproduction

arXiv:2608.24291v1 Announce Type: new Abstract: Paper-to-code reproduction asks scientific AI agents to turn research papers into executable repositories that preserve the paper's method, protocol and

Restoring Without Forgetting: Continual Learning Across Image Degradations

arXiv:2608.23799v1 Announce Type: cross Abstract: Recent progress in image restoration has converged on all-in-one architectures that jointly handle multiple degradations within a single network. Thes

Hardware

Rethinking Pre-Training and Augmentation for Zero-Shot Cross-City Object Detection

arXiv:2608.24154v1 Announce Type: cross Abstract: Real-world deployment of traffic surveillance systems is bottlenecked by geographic domain shift, in which models trained in one city underperform whe

hardwarearxiv-cs-ai

Right Diagnoses, Decorative Reasoning:A Perturbation Audit of Medical Chain-of-Thought

arXiv:2608.24790v1 Announce Type: new Abstract: Clinicians read chain-of-thought (CoT) rationales as evidence of medical reasoning, but whether the visible chain plays that role is rarely tested. Gene

Rubrics as Visual-Repair Context for Self-Evolving UI-to-Code Generation

arXiv:2608.24138v1 Announce Type: new Abstract: Large vision-language models have shown strong progress in UI-to-code generation, yet their test-time self-evolution remains unstable. We first identify

researcharxiv-cs-cv

Scientific Image Synthesis: Benchmarking, Methodologies, and Downstream Utility

arXiv:2601.17027v2 Announce Type: replace-cross Abstract: While synthetic data has proven effective for improving scientific reasoning in the text domain, multimodal reasoning remains constrained by t

Score-Based Ideal Observer Approximation via Denoising Score Matching for Signal-Known-Exactly Detection Tasks

arXiv:2608.24768v1 Announce Type: cross Abstract: The Bayesian Ideal Observer (IO) establishes the theoretical upper bound on task performance for binary detection tasks. However, analytical computati

local-aiarxiv-cs-ai

Segmentation-Guided Homography Estimation for Long-Term Planar Tracking

arXiv:2602.19624v2 Announce Type: replace Abstract: Recent state-of-the-art visual trackers produce high quality and long-term-stable segmentation masks. We propose to leverage these strengths for pla

Tutorials

Spatio-Temporal Garment Reconstruction Using Diffusion Mapping via Pattern Coordinates

arXiv:2602.24043v2 Announce Type: replace Abstract: Reconstructing 3D clothed humans from monocular images and videos is a fundamental problem with applications in virtual try-on, avatar creation, and

tutorialsarxiv-cs-cv

Tlow: Flow-based Item Tokenizer for Recommendation

arXiv:2608.24176v1 Announce Type: cross Abstract: Item tokenizer encodes semantic embeddings into token IDs to replace the randomly assigned item IDs used in traditional recommendation models, fundame

Too much of a good thing -- when knowledge distillation promotes overfitting, and how to avoid it

arXiv:2608.23752v1 Announce Type: cross Abstract: The growing size of Convolutional Neural Networks has led to increasingly large and costly models. Knowledge Distillation (KD) addresses this by trans

safetyarxiv-cs-ai

TorchMorph: CUDA-accelerated Morphological Transforms

arXiv:2608.24738v1 Announce Type: new Abstract: Morphological transforms are long-standing tools for shape and mask processing, but the de facto reference implementation in the Python ecosystem, i.e.

Transformer Accelerator (TFA): A Macro-Op INT8 Hardware Chip for Transformer Inference and Machine Translation

arXiv:2608.23582v1 Announce Type: cross Abstract: We present the Transformer Accelerator (TFA), a synthesizable, parameterizable INT8 memory-to-memory engine for transformer inference. One time-multip

researcharxiv-cs-lg

Trusted Polytopic Action Sets for Fast Planning in Underactuated Systems

model-releasesarxiv-cs-ro

arXiv:2608.24019v1 Announce Type: cross Abstract: Underactuated systems pose a challenge for convex motion planning because their dynamically feasible motions lie on a manifold of trajectories in func

Unlocking the power of partnership: How humans and machines can work together to improve face recognition

arXiv:2510.02570v2 Announce Type: replace Abstract: Human review of consequential decisions by face recognition algorithms creates a collaborative human-machine system. We establish the circumstances

researcharxiv-cs-cv

Variance-Guided Spatial Attention Fusion for Robust End-to-End Driving under Asymmetric Sensor Degradation

arXiv:2608.24366v1 Announce Type: new Abstract: End-to-end multimodal driving has progressed rapidly by fusing camera and LiDAR streams. Existing pipelines remain fragile under asymmetric sensor degra

Velocity-coupled Representation Refinement for Satellite Orbit Prediction

arXiv:2608.23728v1 Announce Type: new Abstract: Satellite orbit prediction, which aims to forecast future orbital trajectories from historical observations, is important for collision warning and safe

researcharxiv-cs-cv

WarpSAC: Towards the Pinnacle of Scalable Off-policy RL by Rethinking Exploration and Exploitation

arXiv:2608.24479v1 Announce Type: new Abstract: Massively parallel simulation changes the data regime in which off-policy reinforcement learning (RL) is trained, challenging stabilizers designed for d

When Do Supervised UQ Ensembles Improve LLM Hallucination Detection? A Robustness Study

arXiv:2608.24492v1 Announce Type: cross Abstract: Uncertainty quantification (UQ) methods are widely used for hallucination detection in large language models (LLMs) in closed-book settings where grou

When 'Must' Becomes 'Maybe': Constraint Weakening in LLM Agent Workflows

arXiv:2608.24569v1 Announce Type: new Abstract: Large language model (LLM) agents coordinate complex tasks through multi-role and multi-stage workflows. Upstream state is repeatedly transformed into i

safetyarxiv-cs-ai

A Comprehensive Analysis of Arabic Natural Language Processing Research: Trends, Topic Evolution, and Research Gaps -- A Bibliometric and Topic-Based Study

arXiv:2608.23421v1 Announce Type: new Abstract: Natural Language Processing (NLP) has grown rapidly over the past decade, driven by digital transformation in the Arab world, social media, and large la

researcharxiv-cs-cl

A Fixed-Radius Distance-Band Benchmark for Dimensionality-Reduction Fidelity

arXiv:2608.21779v1 Announce Type: new Abstract: Dimensionality-reduction (DR) methods are routinely judged by how well each point's k nearest neighbors survive the 2-D embedding (recall@k, trustworthi

Applications

A Momentum-Based Variance-Reduced Algorithm for Federated Multiobjective Optimization

arXiv:2608.22945v1 Announce Type: new Abstract: Federated learning has traditionally been formulated as a single-objective optimization problem, primarily focused on maximizing model utility. In real-

applicationsarxiv-cs-lg

A Source-Grounded Framework for Constructing and Evaluating Progressive Multimodal Diagnostic Dialogues from Clinical Case Reports

model-releasesarxiv-cs-cl

arXiv:2608.22713v1 Announce Type: new Abstract: Clinical diagnosis requires progressive integration of patient history, physical examination, laboratory findings, medical images, and diagnostic-inform

A Unified Neural-Aided Alignment and Calibration Method for AUVs

arXiv:2608.22496v1 Announce Type: new Abstract: Autonomous underwater vehicles (AUVs) rely on the fusion of inertial navigation systems (INS) and Doppler velocity logs (DVL) for accurate navigation. B

safetyarxiv-cs-ro

AcroMELD: Recovering Interactive PDF Forms with Structure-Aware Graph Set Transformers

arXiv:2608.22338v1 Announce Type: new Abstract: Interactive PDF form fields are often absent from documents that visually resemble forms, leaving users unable to enter data without printing or externa

Activation-Weighted Seeded Residual Coding for Low-Bit LLM Weight Repair

arXiv:2608.23144v1 Announce Type: cross Abstract: Low-bit weight quantization saves storage but leaves errors that degrade language-model quality. We introduce Activation-Weighted Seeded Residual Codi

researcharxiv-cs-cl

Align, Unify, Suppress, Route: A Coherentist View of Transformer Computation

arXiv:2608.22034v1 Announce Type: new Abstract: Mechanistic interpretability has identified transformer circuits, but lacks a shared vocabulary for describing how their functions compose across tasks

safetyarxiv-cs-cl

Aligning Human Sense: Calibrated Distributional Reward Learning for Video Generation

arXiv:2608.21425v1 Announce Type: cross Abstract: Video generation is central to AI-powered content creation. Aligning generated videos with human preferences is a key criterion for evaluating generat

local-aiarxiv-cs-ai

AraDetox: A Multi-Dialect Arabic Detoxification Dataset

arXiv:2608.22894v1 Announce Type: cross Abstract: Arabic harmful-language detection has received considerable attention, yet Arabic text detoxification remains underexplored. We introduce AraDetox, a

Bee Detection and Tracking at Hive Entrance using YOLO11 and ByteTrack

arXiv:2608.23213v1 Announce Type: new Abstract: This work presents an automatic bee entrance monitoring system based on YOLO11 transfer learning and the ByteTrack tracking algorithm. The study investi

Agents

Beyond Fresh Starts: Stateful Inference for Streaming ASR in Conversational Voice Agents

arXiv:2608.22101v1 Announce Type: new Abstract: Modern voice-agent systems rely on streaming speech recognition models that operate under stringent latency constraints. This study shows that, due to t

agentsarxiv-cs-lg

Beyond Two Bytes per Letter: Tokenization Overhead in Cyrillic AI Systems

arXiv:2608.21384v1 Announce Type: cross Abstract: Modern multilingual tokenizers often fragment Ukrainian and other underrepresented Cyrillic-script languages more heavily than English, creating dispa