Search: “inference”

Depth-Aware Pothole Detection Using YOLO and RT-DETR at the Edge

arXiv:2608.27633v1 Announce Type: new Abstract: Pothole detection and its severity measurement is still an important challenges in urban infrastructure management, where late maintenance directly cont

safetyarxiv-cs-cv

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GRACE:Gradient-guided Coreset Selection for LLM Unlearning

DGX agent

arXiv:2608.28361v1 Announce Type: cross Abstract: Machine Unlearning methods for Large Language Models typically assume pre-specified forget and retain sets. In realistic settings, however, requests m

researcharxiv-cs-lg

31 Aug 2026

Is Monte Carlo Tree Search Just Every-Visit Monte Carlo Control?

arXiv:2608.27985v1 Announce Type: new Abstract: Monte Carlo Tree Search (MCTS) and every-visit Monte Carlo (MC) control are usually presented as different methods. MCTS is described in the language of

safetyarxiv-cs-lg

Large Reasoning Models Struggle to Transfer Parametric Knowledge Across Scripts

arXiv:2603.17070v2 Announce Type: replace Abstract: In this work, we analyze shortcomings in cross-lingual knowledge transfer in large, modern reasoning LLMs. We demonstrate that the perceived gap in

local-aiarxiv-cs-cl

LayerRecall: A State-Conditioned Memory Router for Long-Horizon Consistency in Video Generation

arXiv:2608.28460v1 Announce Type: new Abstract: Autoregressive video diffusion enables scalable long-video generation by producing chunks from a bounded recent context. While recency-based caching pre

Load-Bearing Context: The Question Damage Score for Evaluating Context Reliance in Linguistic Reasoning

arXiv:2608.27756v1 Announce Type: new Abstract: Determining whether large language models derive answers from context or prior knowledge remains a fundamental challenge. Self-contained linguistic olym

researcharxiv-cs-cl

Localizing Global Discrepancies: Marginal Contributions and Contextual Anomaly Detection

model-releasesarxiv-cs-lg

arXiv:2608.28375v1 Announce Type: cross Abstract: Global goodness-of-fit and discrepancy statistics can establish that a sample departs from a reference distribution without identifying which observat

OpenStamp: A Watermark for Open-Source Language Models

arXiv:2608.27899v1 Announce Type: new Abstract: With the growing prevalence of large language model (LLM) generated content, watermarking is considered a promising approach for attributing text to LLM

researcharxiv-cs-cl

Agents

PACE: Publisher-Adaptive Content Extraction via Agentic Automation

arXiv:2608.27466v1 Announce Type: new Abstract: Web content extraction is essential for reliable LLM data pipelines, yet existing methods often struggle to jointly satisfy accuracy, scalability, and a

agentsarxiv-cs-cl

Performative Privacy: When Differential Privacy Maximizes Utility

arXiv:2608.28198v1 Announce Type: new Abstract: Privacy-preserving learning is often motivated by the idea that protecting users' data can preserve trust and thus participation, improving utility in t

Physics-Guided Flow Matching for CT Image Reconstruction

arXiv:2608.28256v1 Announce Type: cross Abstract: Deep generative models have recently emerged as powerful priors for solving ill-posed inverse problems in CT, with diffusion-based approaches achievin

Plan Along the Way: Event-Triggered Foundation-Model Planning for TAMP Execution in Partially Observable Manipulation

arXiv:2608.28075v1 Announce Type: new Abstract: Manipulation in partially observable environments requires planning under incomplete scene information. In such settings, an initially valid plan may ex

researcharxiv-cs-ro

Prequential posteriors

model-releasesarxiv-cs-lg

arXiv:2511.17721v2 Announce Type: replace-cross Abstract: Data assimilation is a fundamental task in updating forecasting models upon observing new data, with applications ranging from weather predict

Hardware

Quanta Perception as Probabilistic Events

arXiv:2608.27584v1 Announce Type: new Abstract: Autonomous systems rely on extracting information from light, yet remain brittle in extreme environments, from nighttime navigation to high-speed roboti

hardwarearxiv-cs-cv

Quantifying Affective Bias in Low-Resource Media: Large-Scale Emotion Profiling of Bengali Headlines

arXiv:2510.17252v2 Announce Type: replace Abstract: News media can influence readers not only through the events they report but also through the emotional tone used to present them. This issue is esp

Real-Time Monitoring of MHD Liquid Metal Flows with Shallow Recurrent Decoders

model-releasesarxiv-cs-lg

arXiv:2608.28366v1 Announce Type: cross Abstract: State estimation in magnetohydrodynamic flows is critical for real-time monitoring of liquid metal blankets in tokamak fusion reactors. Due to the mul

Relax Forcing: Relaxed KV-Memory for Consistent Long Video Generation

arXiv:2603.21366v2 Announce Type: replace Abstract: Autoregressive video diffusion has recently emerged as a promising paradigm for long-video generation, enabling causal synthesis beyond the temporal

safetyarxiv-cs-cv

Revisiting Local Context for Long-Horizon Streaming 3D Reconstruction

arXiv:2608.27529v1 Announce Type: new Abstract: Streaming 3D reconstruction from extremely long videos requires estimating camera motion and scene geometry online under bounded memory and computation.

RiskBlend: A Multi-Signal Framework for Test Input Prioritization in Machine Learning Regression Testing

arXiv:2608.27704v1 Announce Type: new Abstract: When machine learning classifiers are retrained, inputs correctly classified by the previous model version may be misclassified by the updated version,

local-aiarxiv-cs-lg

SciReC: Diagnostic Evaluation of Multimodal, Multi-Turn Relational Reasoning with Adaptive Interaction

arXiv:2608.27461v1 Announce Type: new Abstract: Relational reasoning requires the process of perceptual understanding, comparing, and integrating the underlying relationships between concepts. This ab

Semantic Head Specialization Guides Hybrid ViT Attention for Multimodal LLMs

arXiv:2608.28383v1 Announce Type: cross Abstract: Hybrid attention dominates frontier LLMs, yet Vision Transformers (ViTs) in multimodal LLMs lack a satisfactory hybrid design, with no consensus on wh

Sledgehammer or Scalpel? A Fine-grained Adaptive Framework for Implicit Hate Speech

arXiv:2608.27462v1 Announce Type: new Abstract: Unlike explicit attacks with obvious profanity, implicit hate speech hides malice within seemingly compliant expressions through metaphors and contextua

SSD: Spatially Speculative Decoding Accelerates Autoregressive Image Generation

arXiv:2606.20543v2 Announce Type: replace Abstract: Autoregressive image models treat images as 1D token sequences, inheriting the next-token factorization of language models. This flattening discards

Temporal Memory-Aware Online Test-Time Adaptation on Dynamic Graphs

arXiv:2608.27948v1 Announce Type: new Abstract: Test-time adaptation (TTA) on graphs aims to adapt a graph neural network (GNN) that is well-trained on the training graph to the test graph, which invo

safetyarxiv-cs-lg

Temporal Tree of Thought: Reasoning-Guided Visual Cue Search for Long-Video Understanding

arXiv:2608.27871v1 Announce Type: new Abstract: Long-video understanding remains challenging for Multimodal Large Language Models (MLLMs) due to limited context length. Uniform sampling may miss cruci

Agents

TI^2PS: A Topology-Informed Inverse Design Framework for Stochastic Multicellular Pattern Formation

arXiv:2608.27931v1 Announce Type: new Abstract: This study proposes a novel framework to estimate parameters for reproducing target multicellular patterns using an agent-based model (ABM). Two major c

agentsarxiv-cs-lg

Token-Budget Distillation: Transferring Full-Token Semantics to Compressed Video Vision-Language Models

model-releasesarxiv-cs-cv

arXiv:2608.28138v1 Announce Type: new Abstract: Adapting video vision-language models (VLMs) is computationally expensive because video inputs produce a large number of visual tokens, making both fine

Trajectory-Level Speculative Decoding for Diffusion Language Models

arXiv:2608.27514v1 Announce Type: new Abstract: Diffusion-based language models (dLLMs) enable parallel token generation through iterative denoising, but existing decoding strategies collapse to singl

researcharxiv-cs-cl

Applications

Var-JEPA: A Variational Formulation of the Joint-Embedding Predictive Architecture - Bridging Predictive and Generative Self-Supervised Learning

arXiv:2603.20111v2 Announce Type: replace Abstract: The Joint-Embedding Predictive Architecture (JEPA) is often seen as a non-generative alternative to likelihood-based self-supervised learning, empha

applicationsarxiv-cs-lg

VidParse: Online Parsing of Egocentric Procedures Like a Pro

arXiv:2608.27562v1 Announce Type: new Abstract: Translating continuous, noisy egocentric video streams into discrete, temporally ordered action steps is fraught with visual challenges. Heavy ego-motio

WALDO: One-Shot Exemplar-Conditioned Object Detection in Cluttered Scenes

arXiv:2608.28216v1 Announce Type: new Abstract: Locating a specific object instance in a cluttered scene using a single reference image and a short description, and reporting when that instance is abs

A Flexible Empirical Bayes Approach to Generalized Linear Models, with Applications to Sparse Logistic Regression

arXiv:2601.21217v2 Announce Type: replace-cross Abstract: We introduce a flexible empirical Bayes approach for fitting Bayesian generalized linear models. Specifically, we adopt a novel mean-field var

A Multi-Framework Comparison of Outline Stages in Long-Form Generation with LLMs

model-releasesarxiv-cs-ai

arXiv:2608.26177v1 Announce Type: cross Abstract: Long-form generation exposes fundamental limitations of large language models. Even 70B-parameter models exhibit length collapse at 16k-token outputs,

Accelerating Scientific Research with Gemini in the Real-World

model-releasesarxiv-cs-ai

arXiv:2608.26701v1 Announce Type: new Abstract: We present an extension and comprehensive real-world validation of Co-Scientist, a Gemini-based multi-agent system designed to accelerate end-to-end sci

Activation Outliers Matter: Robust Recovery for Quantized Multimodal LLMs

arXiv:2608.26581v1 Announce Type: new Abstract: Low-bit quantization offers a promising avenue for reducing the computational and memory demands of Multimodal Large Language Models (MLLMs). Recent har

Active Preference Learning over Latent Preference Archetypes for Many-Objective Bayesian Optimization

arXiv:2603.28410v2 Announce Type: replace Abstract: Preference-based many-objective Bayesian optimization typically assumes that all pairwise comparisons arise from a single latent utility function, d

safetyarxiv-cs-lg

Attention-Guided Reliability Scaling for Contrastive Decoding in Robust Audio-Visual Speech Recognition

arXiv:2608.26213v1 Announce Type: cross Abstract: Large language model (LLM)-based audio-visual speech recognition (AVSR) systems are robust under noise. Contrastive decoding (CD), originally introduc

Bayesian methods and Markov chain Monte Carlo algorithms for curve reconstruction and point cloud data analysis

arXiv:2608.26490v1 Announce Type: new Abstract: Point-cloud data routinely captured by modern imaging and sensor technologies provide detailed geometric descriptions of objects and environments, but t

local-aiarxiv-cs-lg

Behavior2Trip: Towards Personalized Travel Planning via User Behavior Trajectory

model-releasesarxiv-cs-ai

arXiv:2608.26807v1 Announce Type: cross Abstract: Travel planning agents assist users in generating personalized travel plans by modeling their individual preferences. Existing agents either rely on e

Beyond Linearization: Attributed Table Graphs for Table Reasoning

arXiv:2601.08444v2 Announce Type: replace Abstract: Table reasoning, a task to answer questions by reasoning over data presented in tables, is an important topic due to the prevalence of knowledge sto

researcharxiv-cs-ai

CODE: Cross-Modal Calibration and Dynamic Suppression for Open World Object Detection

model-releasesarxiv-cs-cv

arXiv:2608.27214v1 Announce Type: new Abstract: Open World Object Detection (OWOD) built on multimodal foundation models often suffers from semantic ambiguity caused by unidirectional text-to-vision m

Constraint-Aware Physics-Informed Neural Networks for Static Shape Estimation of Co-Manipulative Continuum Robots

arXiv:2608.26273v1 Announce Type: cross Abstract: Static shape estimation of co-manipulative continuum robots (CCRs) is challenging because the continuum arms and manipulated flexible object form a cl

Counterfactual Bias Testing for Application Tracking System

arXiv:2608.26899v1 Announce Type: new Abstract: Automated candidate-job matching systems are increasingly classified as high-risk AI under emerging regulation, yet auditing them for demographic bias i

safetyarxiv-cs-ai

D2C-Routing: Dimension-to-Composition Evidence Routing for Mixed-Origin AI-Generated Text Detection

arXiv:2608.27380v1 Announce Type: new Abstract: AI-generated text detection is commonly framed as a binary document-level judgment about whether a text is human-written or machine-generated. This fram

Applications

Detection of Christmas tree plantations from high-resolution aerial imagery. A case study in the French Morvan

arXiv:2608.27290v1 Announce Type: new Abstract: Christmas tree plantations are economically relevant, yet a largely unexplored application domain in Remote Sensing (RS). Their delineation is challengi

applicationsarxiv-cs-cv

FLARE: A Failure-Aware Framework for Autonomous Correction and Recovery in Visual-Language Robotic Manipulation

arXiv:2608.26645v1 Announce Type: new Abstract: Vision-Language-Action Models~(VLAs) have demonstrated significant promise in generalizing to complex, long-horizon robotic manipulation tasks. However,

safetyarxiv-cs-ro

Generative Monte Carlo Sampling for Constant-Cost Particle Transport

arXiv:2512.13965v1 Announce Type: cross Abstract: We present Generative Monte Carlo (GMC), a novel paradigm for particle transport simulation that integrates generative artificial intelligence directl

GRAFT: Grounded and Efficient Online Reinforcement Adaptation for Fine-Grained Robot Manipulation

arXiv:2608.27079v1 Announce Type: new Abstract: Pretrained vision-language-action (VLA) policies provide strong priors for robot manipulation, yet adapting them online to fine-grained biomedical tasks

safetyarxiv-cs-ro