Search: “benchmark”

arXiv:2609.07094v1 Announce Type: new Abstract: Reasoning is a promising route to the generalization that autonomous driving requires in the long tail, as it can infer how the elements of a scene depe

hardwarearxiv-cs-cv

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CASD: Chunk-Aligned Semantic Distillation for Multi-StageRobot Manipulation

DGX agent

arXiv:2609.08638v1 Announce Type: new Abstract: An action chunk can span several stages of a manipulation task, yet a label for its first step describes only the current stage. We introduce Chunk-Alig

safetyarxiv-cs-ro

9 Sept 2026

CausalChapter: Improving Long-Video Chaptering with Interventional Dependency Modeling

arXiv:2609.08686v1 Announce Type: new Abstract: Long-form instructional videos require automatic chaptering to support browsing, navigation, and knowledge access. Recent long-context language models c

Chimaera: A Mixture-of-Graph-Experts Architecture for Cross-Task and Cross-Dataset Graph Learning

arXiv:2609.08709v1 Announce Type: new Abstract: Designing foundation models for graphs is challenging due to the irregular structure of graphs and the different sizes and characteristics of embeddings

Tutorials

CircuitLens: Reasoning Circuits as Data Selection Signals for Reinforcement Learning with Verifiable Rewards

arXiv:2609.07183v1 Announce Type: cross Abstract: Reinforcement learning with verifiable rewards (RLVR) is sensitive to which problems a model trains on, yet existing selection criteria--difficulty fi

tutorialsarxiv-cs-lg

CogniDir: Combating Cognitive Malicious Comments via Adaptive Distributional Learning for Robust Fake News Detection

arXiv:2510.09712v4 Announce Type: replace Abstract: The proliferation of Large Language Models (LLMs) has enabled a new class of psychologically grounded malicious comments, shifting fake news attacks

ComVLA: Communication-Aware Split Inference for VLA Models in 6G-Connected Robotics

model-releasesarxiv-cs-ro

arXiv:2609.07838v1 Announce Type: new Abstract: Connected robotics is an emerging 6G application where mobile robots follow natural-language instructions to manipulate physical objects. The Vision-Lan

Concentrate After Imagination: Text-Conditioned Evidence Grounding for Partially Relevant Video Retrieval

arXiv:2609.08999v1 Announce Type: new Abstract: Partially Relevant Video Retrieval (PRVR) retrieves untrimmed videos when queries describe only short moments. Although recent methods improve local rep

Condition aware learning enables robust prediction of oligonucleotide melting behavior across diverse chemistries and assay conditions

arXiv:2609.05454v1 Announce Type: cross Abstract: Oligonucleotide melting temperature is a fundamental determinant of nucleic acid hybridization and underpins the design of molecular diagnostics, poly

Local Ai

Content-Based Addressing for Long Context

arXiv:2609.07314v1 Announce Type: cross Abstract: Rotary position embedding (RoPE) uses each token's integer position to determine the rotation applied inside attention. This works well for local toke

local-aiarxiv-cs-lg

Continuous Token-Level Spatio-Temporal Context Modeling for Visual Object Tracking

arXiv:2609.07070v1 Announce Type: new Abstract: Spatio-temporal context has become increasingly crucial for visual tracking. However, most existing approaches extract spatio-temporal cues via discrete

CoRL: Co-Evolutionary Reinforcement Learning for Adaptive Indirect Prompt-Injection Attacks and Defenses

arXiv:2609.07529v1 Announce Type: new Abstract: Tool-augmented language agents are vulnerable to indirect prompt injection (IPI). Unlike direct prompt injection, IPI hides adversarial instructions in

CosmoH2G: A Hand-to-Gripper Transfer Dataset and Baseline Method for Object Manipulation with Complex Spatial Movements

arXiv:2609.07498v1 Announce Type: cross Abstract: Transferring human hand demonstrations to robotic grippers has recently emerged as a cost-effective solution for robot learning. However, existing met

Counterfactual Tests for Measuring Chain-of-Thought Faithfulness in Visual Language Models

arXiv:2609.06704v1 Announce Type: new Abstract: Chain-of-thought (CoT) may often look plausible, yet it may not faithfully reflect the model's decision-making process. While methods for measuring the

CrACK: Adversarial Attacks on Cross-Model Consistency in Collaborative Vision Foundation Models

arXiv:2609.07499v1 Announce Type: new Abstract: Training-free collaborative pipelines that integrate Vision Foundation Models such as CLIP, SAM, and DINO achieve strong open-vocabulary dense predictio

safetyarxiv-cs-cv

Data Efficient Sample Selection for In-Context Learning

arXiv:2609.06670v1 Announce Type: new Abstract: The In-context learning (ICL) paradigm aids large language models (LLMs) to adapt to new tasks without need for fine-tuning. However, selecting an optim

researcharxiv-cs-lg

Detect Anything in Graphic Design: Element-Level Rewards for Autoregressive Detection

arXiv:2609.07072v1 Announce Type: new Abstract: Graphic designs, such as posters, advertisements, and infographics, are an important medium for communicating information and shaping understanding. Unl

safetyarxiv-cs-cv

Applications

Differentiable Causal Discovery for Singular Linear Models under Confounding

arXiv:2601.01368v2 Announce Type: replace Abstract: Score-based causal discovery in the presence of unobserved confounders requires both a consistent scoring criterion and an efficient search over gra

applicationsarxiv-cs-lg

Difficulty-Adaptive Tree-Structured Policy Optimization for Expanding Reasoning Coverage in RLVR

arXiv:2609.08650v1 Announce Type: new Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) has been central to the recent success of Large Reasoning Models. However, while RLVR significantl

Disparity Has a Sign: Stereo Matching Beyond the Zero-Disparity Plane

arXiv:2609.06809v1 Announce Type: new Abstract: Modern stereo matching models fail when disparity crosses zero, with end-point error (EPE) rising by 4.6-37imes. Yet stereoscopic content, from cinema 3

Distillation as Probability Transport: Routed On-Policy Distillation

arXiv:2609.08337v1 Announce Type: new Abstract: On-policy distillation (OPD) transfers teacher knowledge on student-generated trajectories, but efficient sampled objectives reduce the teacher distribu

DL^3M: A Vision-to-Language Framework for Expert-Level Medical Reasoning through Deep Learning and Large Language Models

arXiv:2512.13742v3 Announce Type: replace Abstract: Medical image classifiers detect gastrointestinal diseases well, but they do not explain their decisions. Large language models can generate clinica

Do Quantum AIs Dream in Paths? Path-Integral Slow Thinking through Grover Interference

arXiv:2609.05842v1 Announce Type: cross Abstract: Reinforcement learning with verifiable rewards enables large language models to think slowly, but the same training can induce policy collapse: probab

DPSF-Net: A Dual-Prior Spatial-Frequency Network for Real-World Remote Sensing Image Dehazing

arXiv:2609.06962v1 Announce Type: new Abstract: Real-world remote sensing image dehazing (RSID) remains challenging because atmospheric scattering, spatially non-uniform haze and colour distortion joi

Agents

Drive by Hindsight and Foresight: Tool-Grounded Synergistic Reasoning over Hierarchical Memory for Autonomous Driving

arXiv:2609.08217v1 Announce Type: new Abstract: VLMs have shown promise for autonomous driving, yet still suffer from hallucination, weak spatio-temporal perception, and limited generalization. Recent

agentsarxiv-cs-cv

DriveZero: End-to-End Driving Beyond Human Demonstrations

arXiv:2609.06055v1 Announce Type: new Abstract: Most end-to-end autonomous-driving systems learn by imitating human driving logs, leaving their learned behavior constrained by the quality and behavior

Agents

Driving is a Game: Combining Planning and Prediction with Bayesian Iterative Best Response

arXiv:2512.03936v2 Announce Type: replace Abstract: Autonomous driving planning systems perform nearly perfectly in routine scenarios using lightweight, rule-based methods but still struggle in dense

agentsarxiv-cs-ro

DSE-VTG: Dual-Side Enhancement for Training-Free Video Temporal Grounding

arXiv:2609.08850v1 Announce Type: new Abstract: Text-guided Video Temporal Grounding (VTG) aims to localize the relevant segments in an untrimmed video based on text queries, yet collecting dense temp

DUA-D2C: Dynamic Uncertainty Aware Method for Overfitting Remediation in Deep Learning

arXiv:2411.15876v3 Announce Type: replace-cross Abstract: Overfitting remains a significant challenge in deep learning, often arising from data outliers, noise, and limited training data. To address t

Dual-Layer Semantic-Spatial Belief Mapping for Aerial Object Goal Navigation

model-releasesarxiv-cs-ro

arXiv:2609.08164v1 Announce Type: new Abstract: Aerial Object Goal Navigation (ObjectNav) requires an unmanned aerial vehicle (UAV) to locate a described target in an unknown outdoor environment using

Dynamic System Emulation: Fixed Wing Dynamics on a Multicopter

arXiv:2609.06520v1 Announce Type: cross Abstract: This work presents a control framework that enables a multicopter equipped with a two-axis gimbal to emulate the flight dynamics of a fixed-wing aircr

researcharxiv-cs-ro

Electricity Price Forecasting: Bridging Linear Models, Neural Networks and Online Learning

arXiv:2601.02856v4 Announce Type: replace Abstract: Precise day-ahead forecasts for electricity prices are crucial to ensure efficient portfolio management, support strategic decision-making for power

Eliciting Self-Verification in Multimodal Reasoning Agents with Reinforcement Learning

arXiv:2609.08025v1 Announce Type: cross Abstract: Reasoning agents increasingly rely on external tools such as web search to answer complex queries. Reinforcement learning (RL) finetuning algorithms s

EMBLEM: Enhancing Multi-script Table Detection through Masking

arXiv:2609.08330v1 Announce Type: new Abstract: Table detection is a core task in document analysis, supporting downstream applications such as information retrieval, document reconstruction, and visu

researcharxiv-cs-lg

Endogenous Exploration in Reinforcement Learning with Intrinsic Curiosity

arXiv:2609.05650v1 Announce Type: new Abstract: We propose a reinforcement learning framework in which exploration is driven by intrinsic curiosity, designed for scenarios where environments are non-s

Entropy-Regularized Rank-Masked Policy Optimization for Test-Time Reinforcement Learning in Code Generation

arXiv:2609.09135v1 Announce Type: new Abstract: Existing methods for test-time reinforcement learning (TTRL) derive rewards from answer-level self-voting on unlabeled test-time tasks with canonical an

EntropyPrune: Matrix Entropy Guided Visual Token Pruning for Multimodal Large Language Models

arXiv:2602.17196v2 Announce Type: replace Abstract: Multimodal large language models (MLLMs) incur substantial inference cost due to the processing of hundreds of visual tokens per image. Although tok

Environments as Scaffold: Enriching Feedback to Bootstrap Self-Evolving Agents in Long-Horizon Tasks

arXiv:2609.08404v1 Announce Type: new Abstract: Large Language Models demonstrate remarkable proficiency in static reasoning, yet training them as autonomous agents through Reinforcement Learning (RL)

Evaluation of Contextual Understanding in Large Language Models

arXiv:2609.09004v1 Announce Type: cross Abstract: Large Language Models (LLMs) demonstrate impressive performance across diverse NLP tasks, yet their ability to exhibit genuine contextual understandin

Event-Based De-Snowing for Autonomous Driving

arXiv:2507.20901v2 Announce Type: replace Abstract: Adverse weather conditions, particularly heavy snowfall, pose significant challenges to both human drivers and autonomous vehicles. Traditional imag

FACT: A Forensic Agent with Compiled Tool-Use Trajectories for AI-Generated Image Detection

arXiv:2609.05876v1 Announce Type: new Abstract: AI-generated image detection is increasingly open-world: new image generators produce highly realistic images that make visual artifacts harder to ident

safetyarxiv-cs-cv

FANS: Federated Adaptive Network Search Learning for Heterogeneous Devices

arXiv:2609.06106v1 Announce Type: new Abstract: Heterogeneous Federated Learning (HFL) aims to train models across devices with diverse resource budgets while preserving data privacy. Existing HFL met

Flow-Matching Guided Deep Unfolding for Hyperspectral Image Reconstruction

arXiv:2510.01912v2 Announce Type: replace Abstract: Reconstructing a three-dimensional hyperspectral cube from a two-dimensional compressed measurement is a severely ill-posed inverse problem. Existin

FMMO: Detecting the Divergence Between Local Attribution and Global Drift

arXiv:2609.06173v1 Announce Type: new Abstract: Post-deployment drift poses a critical risk to algorithmic accountability, particularly when ground truth labels are delayed and performance degradation

Applications

FPicker: Topology-Guided Evolution for Filament Tracing in Low-SNR Microscopy

arXiv:2609.08305v1 Announce Type: new Abstract: Automating filament tracing in Cryo-Electron Microscopy (Cryo-EM) is essential for 3D helical reconstruction but challenged by intersecting topologies a

applicationsarxiv-cs-cv

FreeTransformSR: Efficient Lightweight Image Super-Resolution via Free Low-Rank Learnable Transform

arXiv:2609.05912v1 Announce Type: new Abstract: Single image super-resolution aims to reconstruct high-resolution images from low-resolution inputs. This paper proposes FreeTransformSR, a novel lightw

From Explicit References to Scene Manifolds: Distributional Fidelity and Realism for Radiance Field Quality Assessment

arXiv:2609.07346v1 Announce Type: new Abstract: Radiance field representations such as 3D Gaussian Splatting (3DGS) enable high-quality novel view synthesis but can introduce complex, view-dependent a

Agents

From Gaze to Meaning: A Training-Free AI Agent for Unified Grounding and Explanation

arXiv:2609.06208v1 Announce Type: new Abstract: Understanding human attention is fundamental for scene interpretation, yet existing approaches often rely on heavily trained models that lack interpreta

agentsarxiv-cs-cv