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Response Renormalization for Critical Deep Equilibrium Models

model-releasesarxiv-cs-lg

arXiv:2608.23725v1 Announce Type: new Abstract: Deep Equilibrium Models (DEQs) compute predictions from a hidden representation unchanged by the model update. Training through this equilibrium uses im

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Restoring Without Forgetting: Continual Learning Across Image Degradations

DGX agent

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

model-releasesarxiv-cs-ai

26 Aug 2026

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

Retrieval-augmented generation vs. deterministic tax computation in multi-agent financial advisory: A 2x2 factorial experiment

arXiv:2608.23908v1 Announce Type: new Abstract: Tax-loss harvesting demonstrates consistent benefits to long-term portfolio growth; yet implementing it efficiently often involves complex consideration

agentsarxiv-cs-ai

RetrievalFormer: A Dual-Encoder Transformer for Efficient Approximate Nearest Neighbor Retrieval and Cold-Item Recommendation

arXiv:2608.24079v1 Announce Type: cross Abstract: A shared search-and-recommendation index must score new items from features alone because search has no exploration slot. In a public log covering bot

Revelation Control

arXiv:2608.23860v1 Announce Type: cross Abstract: Revelation Control is the problem of choosing priced interventions that reveal hidden state only insofar as the revealed distinctions can change a con

Tutorials

Revenge of Monosemanticity: Specialized Neurons Improve Data Efficiency in MLPs

arXiv:2608.24007v1 Announce Type: new Abstract: Understanding how neural networks learn and organize features is central to understanding their behavior. Much existing theory of feature learning has f

tutorialsarxiv-cs-lg

Review of Explainable Decision Support and Adaptive Human-Machine Interfaces for Automation Transparency in Maritime Autonomous Surface Ships

arXiv:2509.15959v2 Announce Type: replace-cross Abstract: Autonomous navigation in maritime domains is accelerating alongside advances in artificial intelligence, sensing, and connectivity. Opaque dec

agentsarxiv-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

Robust Code RL via Faulty-Code-Driven Test case Synthesis and Dense Reward Shaping

arXiv:2608.24135v1 Announce Type: new Abstract: Reinforcement learning from verifiable rewards (RLVR) has emerged as a pivotal technique for enhancing the code generation capabilities of Large Languag

Robust Data-Collection Policy Learning for Low-Variance Online Policy Evaluation

arXiv:2608.24146v1 Announce Type: new Abstract: In reinforcement learning policy evaluation, classic on-policy methods often suffer from high variance when estimating policy performance. To mitigate t

safetyarxiv-cs-lg

Robust Motion Generation using Part-level Reliable Data from Videos

arXiv:2512.12703v2 Announce Type: replace-cross Abstract: Extracting human motion from large-scale web videos offers a scalable solution to the data scarcity issue in character animation. However, som

Robust Slip Detection and Material Classification via Spatiotemporal Transformers on a Uniformly-Illuminated Visuo-Tactile Sensor

arXiv:2608.24162v1 Announce Type: new Abstract: Tactile sensing is central to robotic manipulation, among which slip detection stands out as a quintessential and critical task. However, existing slip

researcharxiv-cs-ro

RoG-DAgger: Rollout-Guided Post-Training for End-to-End Driving

arXiv:2608.24525v1 Announce Type: new Abstract: Recent end-to-end driving systems demonstrate strong performance on closed-loop benchmarks, yet are still predominantly trained on fixed expert-collecte

safetyarxiv-cs-ro

ROI-Gated SAHI: Content-Adaptive Slicing-Based Inference for Efficient Object Detection

arXiv:2608.23923v1 Announce Type: new Abstract: Slicing-Aided Hyper Inference (SAHI) improves small object detection in high-resolution images but often spends substantial compute on background tiles.

safetyarxiv-cs-cv

Round-trip Reinforcement Learning: Self-Consistent Training for Better Chemical LLMs

arXiv:2510.01527v2 Announce Type: replace Abstract: Large Language Models (LLMs) are emerging as versatile foundation models for computational chemistry, handling bidirectional tasks like reaction pre

RT-NeuS: Towards Real-Time Neuro-Symbolic Video Understanding via Adaptive Temporal Verification

arXiv:2602.23553v2 Announce Type: replace Abstract: Long-form video question answering (LVQA) requires answering natural-language queries about videos spanning minutes to hours, demanding temporal rea

hardwarearxiv-cs-cv

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

Rules Before Oracles: Auditable, User-Configurable Argument Selection for Deliberative Polling

arXiv:2608.23979v1 Announce Type: new Abstract: In a deliberative poll, once submissions outnumber what anyone will read, some mechanism chooses which arguments each voter sees, acquiring much of the

safetyarxiv-cs-ai

Tutorials

S-matrix informed neural networks for amplitude analysis

arXiv:2608.23750v1 Announce Type: cross Abstract: Reconstructing scattering amplitudes from finite, noisy, and mutually inconsistent measurements is an ill-posed inverse problem common to many reactio

tutorialsarxiv-cs-lg

SA-Bench: Evaluating Semantic Alignment in LLM-Based Paper Reproduction

arXiv:2608.24252v1 Announce Type: new Abstract: LLM agents can generate paper reproduction code, yet often produce scientifically unfaithful implementations. We define this failure mode as semantic dr

Safety-aware Model Predictive Path Integral Control with Signal Temporal Logic

arXiv:2608.23972v1 Announce Type: new Abstract: Safety-aware motion planning remains a challenge in robotics, especially when missions are time-critical and are under complex specifications. In this p

safetyarxiv-cs-ro

SAGE: From Direct Answering to Evidence-Grounded Inference for Chinese Ancient Document Understanding

arXiv:2608.24011v1 Announce Type: cross Abstract: Chinese ancient document understanding demands complex visual, linguistic, and historical reasoning. Current Large Vision-Language Models (LVLMs) typi

SandwichQuant: Which Parameters Matter Before and After Quantization?

model-releasesarxiv-cs-cv

arXiv:2608.24173v1 Announce Type: new Abstract: Quantization correction methods usually optimize weights, quantization parameters, or reconstruction objectives, while the underlying parameter subspace

SatDL: Jointly Optimizing Data Redistribution and Training for Satellite-Based Distributed Learning

arXiv:2608.24516v1 Announce Type: cross Abstract: Satellite-based distributed learning promises to train machine-learning models directly in orbit using massive, globally dispersed sensor data, thereb

hardwarearxiv-cs-lg

Scalable and Versatile Identification for Hierarchical Structural Causal Models: A New Look at Project STAR

arXiv:2608.24500v1 Announce Type: cross Abstract: The STAR (Student-Teacher Achievement Ratio) experiment (1985, Tennessee, USA) is a landmark hierarchical dataset designed to assess the impact of cla

Scalable Question-Centric Text-to-Image Evaluation: Reliable Ranking, Fine-Grained Diagnosis, and Cost-Aware Routing

arXiv:2608.24112v1 Announce Type: new Abstract: Modern text-to-image (T2I) models often have similar total scores but different strengths, making practical selection difficult. Fine-grained benchmarks

Scaling Reinforcement Learning for Diffusion Models via Velocity Matching

arXiv:2608.23664v1 Announce Type: new Abstract: Reward fine-tuning is becoming an important tool for adapting diffusion models to human preferences and task-specific objectives, but existing methods l

safetyarxiv-cs-cv

SceneReGen: Generative Reconstruction of 3D Scenes from a Single Image

arXiv:2608.23930v1 Announce Type: new Abstract: Single-image 3D scene reconstruction must complete partially observed objects and place them coherently in a shared observation-aligned scene frame. Obj

agentsarxiv-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

Local Ai

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

Screening Autism Spectrum Disorder in children using Deep Learning Approach : Evaluating the classification model of YOLOv26s by comparing with other models

arXiv:2306.14300v2 Announce Type: replace-cross Abstract: Autism spectrum disorder (ASD) is a developmental condition that presents significant challenges in social interac- tion, communication, and b

Segmentation-Guided Homography Estimation for Long-Term Planar Tracking

model-releasesarxiv-cs-cv

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

SeisMamba: Low-Latency Single-Station Seismic Magnitude Estimation for Spatially Distributed Earthquake Early Warning

model-releasesarxiv-cs-lg

arXiv:2608.24561v1 Announce Type: new Abstract: Rapid earthquake magnitude estimation is central to earthquake early warning, yet many operational systems depend on dense regional seismic networks and

Selective Regenerative Decoding: Trajectory-Level Intervention for Inference-Time Reasoning

arXiv:2608.24338v1 Announce Type: new Abstract: Inference-time decoding methods improve LLM reasoning by exploring multiple candidate trajectories, yet treat each trajectory as atomic: either retainin

Semantic Overlays: Mitigating Prompt Injection with Annotations Beyond Tokens and Steering Vectors

arXiv:2608.23873v1 Announce Type: new Abstract: Everything a language model sees is tokens. The serving stack knows what each span is -- user input, tool output, instructions -- but the model must kee

SeMoCo: A Semantic-First Motion Codec for Motion Language Modeling

arXiv:2608.24334v1 Announce Type: new Abstract: Discrete motion representations have substantially advanced autoregressive text-to-motion generation. However, most motion tokenizers are optimized for

researcharxiv-cs-cv

SENSESHIFT: Continuous Sentiment-Controlled Text Generation via Encoder-based Mask Infilling

arXiv:2608.24304v1 Announce Type: cross Abstract: Recent controllable text generation (CTG) for sentiment control has largely focused on decoder-based large language models, making causal attention th

Sensorless damage-safe grasping

model-releasesarxiv-cs-ro

arXiv:2608.23983v1 Announce Type: new Abstract: Robotic fruit harvesting must hold produce securely without bruising it, yet compression stiffness varies several-fold with ripeness within a single spe

Sequential operator learning under dependent data

arXiv:2608.24426v1 Announce Type: cross Abstract: Learning operators from sequentially collected data arises in adaptive experimental design, Bayesian optimization, and dynamical-system modelling, whe

Serving Masked Diffusion LLMs: Characterization and Design Principles from Real Hardware

arXiv:2608.23807v1 Announce Type: new Abstract: Masked diffusion language models (dLLMs) can in principle generate text faster than autoregressive (AR) models, since they denoise many tokens at once.

ShardMeter: Sharded and Geo-Distributed Training Without the Guesswork

arXiv:2608.23840v1 Announce Type: cross Abstract: Training large-scale AI models often outgrows a single data center, demanding sharded, multi-cluster, and decentralized training. However, the huge sp

Simthesizer: An Agent-Driven Simulation Framework for LLM Serving Systems

arXiv:2608.24650v1 Announce Type: cross Abstract: System-level simulation is an essential tool for exploring the rapidly expanding design space of LLM serving systems, where real deployments remain co

agentsarxiv-cs-ai

Single State Update Predictive Coding training for Time Series Forecasting and Anomaly Detection

arXiv:2608.24697v1 Announce Type: new Abstract: Predictive Coding (PC) is a neural learning paradigm that enables parallelizable neural network layer updates. However, the main bottleneck of PC Networ

Single-Subject Multi-View MRI Super-Resolution via Implicit Neural Representations

arXiv:2603.22627v2 Announce Type: replace-cross Abstract: Clinical MRI frequently acquires anisotropic volumes with high in-plane resolution and low through-plane resolution to reduce acquisition time

safetyarxiv-cs-cv

SIREN-Bench: Behavior-Driven Generation and Evaluation of Emergency-Vehicle Interactions

model-releasesarxiv-cs-ro

arXiv:2608.24094v1 Announce Type: new Abstract: Emergency vehicles (EMVs) can reorganize surrounding traffic as civilian vehicles brake, change lanes, or form rescue corridors in response to their pas

SonarLLM: A Native Sonar--Optical Multimodal Large Language Model for Underwater Perception

arXiv:2608.24325v1 Announce Type: new Abstract: Reliable underwater perception requires complementary sensing under variable visibility. Optical cameras capture appearance and semantics but degrade ra

Source-Face Authenticity Detection for 3D Gaussian Heads Reconstructed from a Single Portrait: A Benchmark and Dedicated Detector

model-releasesarxiv-cs-cv

arXiv:2608.23984v1 Announce Type: new Abstract: Recent advances in single-image 3D Gaussian head reconstruction have enabled highly realistic and freely renderable digital heads from a single portrait