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Restrict, Don't Retrain: Inference-Time VLM Guidance for Zero-Shot Aerial Segmentation

arXiv:2609.00628v1 Announce Type: cross Abstract: Global welfare often depends on the correct interpretation of aerial and satellite imagery. Acting on such imagery (mapping flooded ground, crop exten

local-aiarxiv-cs-ai

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Rethinking Learnability in Offline Data-driven Optimization

DGX agent

arXiv:2609.01493v1 Announce Type: cross Abstract: Black-Box Optimization (BBO) has found broad applications, but evolutionary algorithms and Bayesian optimization face efficiency challenges as real-wo

applicationsarxiv-cs-ai

2 Sept 2026

Retrieval, Scoring, and Decoding Shape Performance and Stability in LLM-based Conversational Recommendation

arXiv:2609.00086v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used as rerankers in conversational recommender systems, yet measured gains depend strongly on the retri

Retrieved but not ranked: surface-form bias in structural retrieval, from mathematics to agent trajectories

arXiv:2609.01556v1 Announce Type: cross Abstract: We evaluate embedding retrieval where surface form and meaning are pulled apart on purpose: retrieving items that share underlying structure but not w

Revealing Multi-View Hallucination in Large Vision-Language Models

arXiv:2603.23934v2 Announce Type: replace-cross Abstract: Large vision-language models (LVLMs) are increasingly being applied to multi-view image inputs captured from diverse viewpoints. Despite this

REVISE: Validity-Guided Recovery for Online Revisions in Agent Workflows

arXiv:2609.00643v1 Announce Type: new Abstract: Agent revisions expose a fundamental correctness--efficiency trade-off during concurrent execution. Discarding ongoing work preserves latest-version cor

Revisiting Cross-View Completion: Self-Supervised Pre-Training via Reconstruction Error Comparison

arXiv:2609.01530v1 Announce Type: new Abstract: Self-supervised pre-training via cross-view completion learns strong features for 3D vision from co-visible regions of image pairs. However, the referen

Revisiting Face Recognition for Monozygotic Twins: The Celeb Twins Test Set

arXiv:2609.01141v1 Announce Type: cross Abstract: Past literature on face recognition for monozygotic (('identical') twins points to facial marks and mirror asymmetry as possible directions for improv

Right Frame, Wrong Rule: Cultural Cues Expose the Financial Knowledge Gap They Were Meant to Close

arXiv:2609.00999v1 Announce Type: cross Abstract: When a question has valid answers under different normative frameworks, a language model must decide which framework to use and whether it can answer

Rigorous Error Certification for Neural PDE Solvers: From Empirical Residuals to Solution Guarantees

arXiv:2603.19165v2 Announce Type: replace Abstract: Uncertainty quantification for partial differential equations is traditionally grounded in discretization theory, where solution error is controlled

researcharxiv-cs-lg

RingMoClaw: An Experience-Inspired Multi-Agent Framework for Self-Evolving Research in Remote Sensing

arXiv:2609.00814v1 Announce Type: new Abstract: Remote sensing visual models have continuously advanced various interpretation tasks. However, the research process behind model improvement still heavi

agentsarxiv-cs-cv

Risk-Aware Decision-Making for Autonomous Overtaking: A World Model-Based Mixture-of-Experts Framework

arXiv:2609.00385v1 Announce Type: cross Abstract: Autonomous highway overtaking demands foresighted decision-making to handle complex interactions, stochastic traffic evolution, and temporal risk accu

local-aiarxiv-cs-ai

Rock, Paper, Scissors, ... Dynamite - A Model of Disruption from New Technologies

arXiv:2609.00207v1 Announce Type: cross Abstract: We seek to understand the effect of adding disruptive highly-capable new technologies to competitions by assessing the addition of Dynamite to Rock-Pa

RPCBench: A Benchmark for Proactive Premise Critique in LLM-based Recommendation

arXiv:2609.00918v1 Announce Type: new Abstract: Large language models are increasingly used as interactive recommender assistants. Their evaluation should therefore go beyond plausible item recommenda

Runtime-Independent Persistent Agents: Preserving Identity, Memory, and Code Across Models, Harnesses, and Servers

arXiv:2609.00546v1 Announce Type: cross Abstract: Agent systems are commonly described by the model and harness that currently produce their behavior. That boundary is useful for one execution but und

RW-LoRA: Communication-Efficient Decentralized LoRA Fine-Tuning via Random Walks

arXiv:2609.00078v1 Announce Type: cross Abstract: Parameter-efficient fine-tuning methods such as LoRA have become a standard approach for adapting large foundation models. Adopting fine-tuning to dis

S^2Prune: Spatially Structured Visual Token Pruning for Multimodal Large Language Models

arXiv:2609.01224v1 Announce Type: new Abstract: Visual token pruning reduces the inference overhead of multimodal large language models (MLLMs) by retaining only a subset of visual tokens. Existing me

local-aiarxiv-cs-cv

S^3martCirc: Self-supervised Smart Circuit Discovery

arXiv:2609.00755v1 Announce Type: new Abstract: Large Language Models (LLMs) have demonstrated remarkable performance across diverse tasks, from text summarization to question answering. Despite these

Safin-1: Safety from Within through Memory-Native State Evolution

arXiv:2609.00092v1 Announce Type: new Abstract: Long-horizon complex tasks require foundation models to accumulate information, maintain internal states, and adapt over extended interactions. Safety s

safetyarxiv-cs-lg

SAGE: State-Grounded, Abstention-Aware Evaluation of Task-Oriented Dialogue Agents

arXiv:2609.00434v1 Announce Type: new Abstract: Evaluating task-oriented dialogue agents requires judging not merely whether a reply reads well but whether each turn advances the underlying workflow s

SAGE: Subpopulation-Aware Generative Enhancement for Mitigating Spurious Correlations

arXiv:2609.01051v1 Announce Type: cross Abstract: Spurious correlations pose a significant challenge to the robustness of modern machine learning. The inherent imbalance in dataset distributions often

researcharxiv-cs-cv

SAM3-LoRA: Parameter-Efficient Adaptation of a Concept-Promptable Foundation Model for Multi-Class Structural Defect Segmentation

arXiv:2609.00469v1 Announce Type: new Abstract: Promptable segmentation foundation models such as SAM3 accept an open-vocabulary text concept and return every instance matching it, but adapting them t

Same Request, Different Boundary: Evaluating Cybersecurity Assistance across Conversational Contexts

arXiv:2609.00578v1 Announce Type: new Abstract: Large Language Models (LLMs) can solve complex problems, but their misuse in high-risk domains can lead to severe consequences. Model providers therefor

Same Semantics, Different Outcome: On the Modality Robustness of Multimodal LLMs under Knowledge Conflict

arXiv:2609.00550v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) are increasingly provided with contextual evidence in heterogeneous forms: as a text passage, as a rendered ima

researcharxiv-cs-cl

SARTM: Segment Any RGB Thermal Model with Language aided Distillation

arXiv:2505.01950v2 Announce Type: replace-cross Abstract: The recent Segment Anything Model (SAM) demonstrates strong instance segmentation performance across various downstream tasks. However, SAM is

Tutorials

SCAFFOLD: A Large-Scale Structured Dataset of Computer Science Research Figures with Diagram QA and Chain-of-Thought Reasoning Traces

arXiv:2609.00018v1 Announce Type: new Abstract: Computer science papers rely heavily on diagrams: architecture drawings, system flowcharts, and pipeline schematics that often carry more information th

tutorialsarxiv-cs-ai

Scalable Rao-Blackwellized Online Planning for High-Dimensional POMDPs

arXiv:2609.01351v1 Announce Type: cross Abstract: Online planning under uncertainty remains a fundamental challenge for robotic systems operating in partially observable environments with high-dimensi

Scale-based Approach for Active Wildfire Segmentation on Satellite Imagery

arXiv:2609.01392v1 Announce Type: new Abstract: Active wildfire mapping from satellite imagery is challenging due to the sparse and highly imbalanced nature of fire pixels, especially in early-stage o

researcharxiv-cs-cv

Scaled Idempotence in Transformer Attention: Paired OV Geometry and Shared-Value Algebras

arXiv:2609.01129v1 Announce Type: new Abstract: We identify a recurrent algebraic regularity in Transformer attention: a sparse subset of effective OV operators T=OV^op nearly closes under composition

safetyarxiv-cs-lg

Tutorials

SCALE:Scalable Conditional Atlas-Level Endpoint transport for virtual cell perturbation prediction

arXiv:2603.17380v3 Announce Type: replace-cross Abstract: Virtual-cell models aim to predict how cell populations respond to perturbations, but control and treated cells are measured as unpaired popul

tutorialsarxiv-cs-ai

Scaling Near-Optimal SFT-RL Annotation Budget Allocation from Small to Large LLMs

arXiv:2609.01573v1 Announce Type: cross Abstract: How to divide a fixed annotation budget between supervised fine-tuning (SFT) and reinforcement learning (RL) during LLM post-training remains an open

Scene Graph-based Driving Scenario Extraction for Automotive Egocentric Datasets

model-releasesarxiv-cs-ro

arXiv:2609.00333v1 Announce Type: new Abstract: Extracting scenarios from unlabelled real-world sensor data streams is a critical but challenging task in the development process of automated driving s

Scientific Agent Skills: A Library of Procedural Knowledge for Research Agents

arXiv:2609.00065v1 Announce Type: cross Abstract: A language-model agent asked to analyse an experiment will usually return working code. Whether the analysis is defensible is a different question. A

SciTrue: Reliable Scientific Claim Validation with Frontier and Open Language Models at the NTCIR SciClaimEval Task

arXiv:2609.00654v1 Announce Type: new Abstract: We describe the SciTrue team's participation in both subtasks of the NTCIR-19 SciClaimEval task~ite{sciclaimeval}, which asks systems to verify scientif

SCoNE: Selective Context-aware Neuron Editing for Robust Retrieval-Augmented Generation

arXiv:2609.00689v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) is highly sensitive to retrieval noise: when retrieved documents mix informative and irrelevant context, LLMs are e

researcharxiv-cs-cl

Scope3Trace: Evidence-Based Identification and Extraction of Scope 3 GHG Emissions from Sustainability Reports

arXiv:2607.17122v2 Announce Type: replace Abstract: Scope 3 greenhouse gas (GHG) emissions account for the majority of corporate carbon footprints, yet remain difficult to analyze at scale due to spar

local-aiarxiv-cs-cl

SDARE-Bench: Evaluating Large Language Models on Conversational Stigma Detection and Response in Dyadic and Group Dialogue

model-releasesarxiv-cs-cl

arXiv:2609.01548v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly used in advice seeking and decision making that may affect social judgements. Despite stigma's profound ef

Applications

SEBA: Sample-Efficient Black-Box Attacks on Visual Reinforcement Learning

arXiv:2511.09681v2 Announce Type: replace-cross Abstract: Visual reinforcement learning has achieved remarkable progress in visual control and robotics, but its vulnerability to adversarial perturbati

applicationsarxiv-cs-ai

Seeing the World and the Self from Egocentric Video

arXiv:2609.01276v1 Announce Type: new Abstract: Complete 3D perception from egocentric video requires recovering the surrounding scene and the wearer's full-body motion in a shared metric frame. Exist

researcharxiv-cs-cv

SeerGuard: A Safety Framework for Mobile GUI Agents via World Model Prediction

arXiv:2607.15550v2 Announce Type: replace Abstract: Mobile graphical user interface (GUI) agents have demonstrated remarkable capabilities in automating complex tasks, yet they introduce critical safe

Selective Agent Guidance via Entropy: Learning Autonomous Policies from Imperfect VLM Teachers

arXiv:2609.01567v1 Announce Type: new Abstract: Vision-Language Models (VLMs) provide useful priors for interactive decision-making, but using them directly as policies is expensive and brittle: they

Self-Reports Are Not Verification: Environment-Grounded Auditing of LLM Operators in Evolutionary Search

arXiv:2609.00652v1 Announce Type: new Abstract: Language model agents increasingly propose actions, observe external feedback, and explain their own behavior. Their confidence and rationales are conve

Semantic-Guided Multimodal Preprocessing for Vision Transformer-Based Clear Cell Renal Cell Carcinoma Grading

arXiv:2609.01426v1 Announce Type: cross Abstract: Clear cell renal cell carcinoma (CCRCC) grading is essential for treatment planning, yet existing approaches either analyze patch-level images directl

Semi-Supervised Biomedical Image Segmentation via Diffusion Models and Teacher-Student Co-Training

arXiv:2504.01547v3 Announce Type: replace Abstract: Supervised deep learning achieves strong performance in biomedical image segmentation but relies on costly pixel-wise annotations, motivating semi-s

Semi-Supervised Classification with Informative Missing Labels in Weibull Mixture Models

arXiv:2609.00774v1 Announce Type: cross Abstract: We consider semi-supervised classification from a partially classified sample arising from a two-component Weibull mixture. The feature is observed fo

researcharxiv-cs-lg

Tutorials

Semi-Supervised Virtual Staining via Morphology Preservation and Histopathological Realism Constraints

arXiv:2609.00984v1 Announce Type: cross Abstract: Virtual staining aims to computationally generate target-stained histopathological images while reducing the cost and time associated with conventiona

tutorialsarxiv-cs-ai

Separating perception from reasoning in vision-language models: a model-free render ceiling for crystal structures

arXiv:2609.00663v1 Announce Type: new Abstract: Multimodal evaluations cannot say whether a vision-language model misread an image or misreasoned about it, because every existing method for separating

Applications

Separating Syntax from Language: A Mechanistic Account of Translation in Multilingual LLMs

arXiv:2609.01356v1 Announce Type: new Abstract: Multilingual large language models (mLLMs) achieve strong performance in machine translation, yet our understanding of the mechanisms by which they tran

applicationsarxiv-cs-cl