Search: “benchmark”

Listen Then Reason: Perception-Grounded Test-Time Reinforcement Learning for Large Audio-Language Models

arXiv:2609.23589v1 Announce Type: cross Abstract: Large audio-language models (LALMs) are increasingly used for a broader range of audio reasoning tasks. These models typically incorporate audio repre

researcharxiv-cs-ai

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Research

LLaVA-Assessor: Building the Foundation LMM For Visual Quality Assessment

DGX agent

arXiv:2609.26205v1 Announce Type: new Abstract: Aligning with the human visual system~(HVS) in perceiving and evaluating the quality of visual signals is a central objective of machine-vision-based vi

researcharxiv-cs-cv

23 Sept 2026

MAGIC: Mixed-Granularity Agent Graphs via Incremental Construction with Dense-Reward Reinforcement Learning

arXiv:2609.26667v1 Announce Type: new Abstract: Collaboration topology shapes both the performance and execution cost of LLM-based multi-agent systems. Because tasks differ in complexity and required

local-aiarxiv-cs-lg

Matryoshka attribution: Learning to attribute language model outputs to representations and weights

arXiv:2609.25518v1 Announce Type: new Abstract: Attributing language model outputs to their internal computations is an open problem in interpretability. Existing methods, which use causal interventio

MedRSI: Recursive Self-Improvement for Medical Agents via Clinically Aligned Self-Evolution

arXiv:2609.24838v1 Announce Type: new Abstract: Medical agents increasingly combine general reasoning models with specialized clinical tools, yet their capabilities remain largely fixed by what clinic

safetyarxiv-cs-ai

Applications

Memory-Free Continual Learning with Null Space Adaptation for Zero-Shot Vision-Language Models

arXiv:2510.21175v2 Announce Type: replace Abstract: Pre-trained vision-language models (VLMs), such as CLIP, have demonstrated remarkable zero-shot generalization, enabling deployment in a wide range

applicationsarxiv-cs-ai

MGRL-RSCC: Multi-Granularity Reward Reinforcement Learning for Fine-Grained Remote Sensing Change Captioning

arXiv:2609.26166v1 Announce Type: cross Abstract: Remote Sensing Change Captioning (RSCC), which aims to generate accurate and detailed linguistic descriptions of ground object variations from bi-temp

MIAR: Medical Image Super-Resolution With Autoregressive Modeling

arXiv:2609.26103v1 Announce Type: new Abstract: Medical Image Super-Resolution (MISR) aims to enhance spatial resolution without requiring hardware modifications. Although deep learning has yielded pr

MicroPush: A Lightweight Simulator for Sim-to-Real Microrobotic Pushing and Assembly

arXiv:2602.23607v2 Announce Type: replace Abstract: Developing learning-based autonomy for microrobotic manipulation is difficult because physical trials are slow, variable, and poorly suited to large

safetyarxiv-cs-ro

Tutorials

Minimal Recurrent Behavioral Memory for Imitation under Partial Observability

arXiv:2609.25757v1 Announce Type: new Abstract: What is the least recurrent memory needed to reproduce a specified expert under partial observability? The instantaneous requirement is the conditional

tutorialsarxiv-cs-lg

Mining Legal Arguments in U.S. Corporate Case Law

arXiv:2609.25441v1 Announce Type: new Abstract: Legal argument mining supports passage classification, retrieval, and argument completion. This work introduces an expert-annotated dataset of 42 U.S. f

MirrorDistill: Illumination-Aware Latent Distillation for Efficient Low-Light Restoration

arXiv:2609.25331v1 Announce Type: new Abstract: Low-light image enhancement (LLIE) is an im- portant component of visual sensing systems operating under degraded illumination, including nighttime surv

safetyarxiv-cs-cv

MorphoSHAP: Rethinking the Unit of Attribution in Explanation for Deep Visual Models

arXiv:2609.25815v1 Announce Type: new Abstract: Visual attribution methods typically explain predictions using pixels, superpixels, or regular patches. These representations can localize important reg

local-aiarxiv-cs-cv

Multi-View Fair Clustering Guided by Cross-View Sensitive Information Discrepancy

arXiv:2609.25811v1 Announce Type: new Abstract: Multi-view clustering (MVC) aims to uncover latent cluster structures by exploiting complementary information from multiple views. Despite substantial p

NaCR: Visual Localization via NeRF-aided Camera Ray Regression

arXiv:2609.25907v1 Announce Type: new Abstract: Visual localization (VL) is a fundamental technology for vision applications such as virtual reality. Recently, a novel VL paradigm, Camera Ray Regressi

local-aiarxiv-cs-cv

Agents

NostrAgent: A Decentralized Identity and Delegation Architecture for Sovereign Agentic Systems

arXiv:2609.22944v1 Announce Type: cross Abstract: Autonomous AI agents increasingly act across organizational boundaries on behalf of human operators: they invoke third-party services, delegate subtas

agentsarxiv-cs-ai

NPU Accelerator: Quantized Real-Time Vehicle Detection on PYNQ-Z1 Using FINN

arXiv:2609.24757v1 Announce Type: cross Abstract: This paper presents the design, optimization, implementation, and on-board validation of a neural processing unit (NPU) accelerator for real-time vehi

researcharxiv-cs-ai

OMatG-flash: An All-Atom Flow Map with Reinforce Adjoint Matching for Scalable Materials Discovery

arXiv:2609.26402v1 Announce Type: new Abstract: The discovery of novel inorganic materials drives technological breakthroughs in critical fields such as computing and energy storage. Generative AI has

OmniEcho: Spatial Audio Understanding for Embodied Agents

model-releasesarxiv-cs-ai

arXiv:2609.23407v1 Announce Type: cross Abstract: Humans can effortlessly localize the direction of a sound source and integrate it with visual cues for reasoning, yet this remains challenging for emb

On Basis Function Selection for Sparse Gaussian Process Regression

arXiv:2609.26624v1 Announce Type: cross Abstract: Sparse Gaussian processes achieve O(N) inference by replacing the kernel with an appropriate expansion in a fixed basis {phi_j} on the input space. Gi

researcharxiv-cs-lg

Optimizing Denoising Trajectories in dLLMs: A Lightweight Evolutionary Heuristic Approach

arXiv:2609.26052v1 Announce Type: new Abstract: Diffusion Large Language Models (dLLMs) have recently emerged as a promising alternative to conventional Auto-Regressive (AR) Large Language Models (LLM

OptiSkill: A Hierarchical and Evolving SkillBank for LLM-Based Optimization Modeling

arXiv:2609.22987v1 Announce Type: new Abstract: Automated operations research (OR) modeling requires LLMs to translate natural-language decision problems into correct mathematical programs. Existing m

local-aiarxiv-cs-ai

PACE-dLLM: Elastic Block Decoding via Confidence Cliff Estimation for Diffusion Language Models

arXiv:2609.26249v1 Announce Type: new Abstract: Diffusion language models (dLLMs), such as LLaDA and Dream, have become competitive with autoregressive (AR) LLMs in generation quality while supporting

researcharxiv-cs-cl

PACT: From Credit Assignment to Critic Alignment

arXiv:2609.26355v1 Announce Type: new Abstract: Reinforcement learning has become a central component of large language model (LLM) post-training, yet token-level credit lacks a generally accepted mat

safetyarxiv-cs-lg

PAKT: Physically-Aligned Kinesthetic Teaching for Reinforcement Learning

arXiv:2609.25630v1 Announce Type: new Abstract: Real-world reinforcement learning (RL) systems still struggle with the demands of contact-rich industrial manipulation, including micrometer-level preci

safetyarxiv-cs-ro

PARTE: Plane-Assisted Robust Transformation Estimation for Point Cloud Registration

arXiv:2609.25375v1 Announce Type: new Abstract: Global point-cloud registration remains challenging when limited overlap, repetitive geometry, and sensor noise produce correspondence sets dominated by

researcharxiv-cs-ro

PINNForge: Execution-Grounded Evolutionary Design of Physics-Informed Neural Networks for PDE Solving via Large Language Models

arXiv:2609.23023v1 Announce Type: new Abstract: Physics-informed neural networks (PINNs) require coordinated choices over network representation, sampling, loss construction, and optimization, while e

researcharxiv-cs-ai

Point Diffusion Mamba: Unified Diffusion-State-Space Modeling for Single-View 3D Reconstruction under Data Scarcity

arXiv:2609.25538v1 Announce Type: new Abstract: While single-view 3D reconstruction has seen significant progress, extrapolating complex 3D structures from inherently ambiguous 2D observations remains

PP-Net: A Hybrid Physical-Prior Neural Network for Scattered Light Removal in Biomedical Images on Embedded Devices

arXiv:2609.26474v1 Announce Type: cross Abstract: Scattered light is common in biomedical images, yet its removal remains challenging. The difficulty arises from three aspects: first, aligned scattere

researcharxiv-cs-lg

QuantWM: Temporally Consistent 2-Bit KV Cache Quantization for World Models and Video Generation

arXiv:2609.26425v2 Announce Type: new Abstract: KV cache memory has become a major deployment bottleneck for video generation and world models, which motivates low-bit quantization study for efficienc

RankCert: When Can Simulated Learners Safely Select an AI Tutor? Robust Decision Certification Under Structural Uncertainty

arXiv:2609.26069v1 Announce Type: cross Abstract: Simulation-based tutor selection can be unstable when predictively adequate learner models imply different policy rankings. RankCert certifies one of

Tutorials

Reading Right, Answering Wrong: How Visual Configuration Changes Affect Evidence Use in VLMs

arXiv:2609.25770v1 Announce Type: new Abstract: Vision-language models (VLMs) have achieved strong performance on tasks such as visual question answering, yet small image resizes can turn correct answ

tutorialsarxiv-cs-cv

ReasonLab: A Controlled and Auditable Evaluation of Prompting Techniques for Multiple-Choice QA

arXiv:2607.14109v2 Announce Type: replace Abstract: Probing the capabilities of Large Language Models (LLMs) and building robust solutions for Multiple-Choice Question Answering (MCQA) remain central

researcharxiv-cs-cl

RGSQ: Riemannian Geometry-Sensitive Quantization for Large Vision-Language Models

arXiv:2609.25492v1 Announce Type: new Abstract: Large vision-language models (VLMs) can be efficiently deployed under stringent memory and latency constraints through post training quantization (PTQ).

ROAM-ASD: Robust Open-World Active Speaker Detection with Flexible Multimodal Fusion

arXiv:2609.26648v1 Announce Type: cross Abstract: Active speaker detection (ASD) requires reliable association between visible faces and acoustic speech, yet existing systems often degrade under chall

RoboFollow: Unveiling the Instruction Following Mirage in Embodied Agents

model-releasesarxiv-cs-ro

arXiv:2609.25636v1 Announce Type: new Abstract: Modern embodied agents achieve impressive success rates, yet their actual instruction-following ability is far weaker than these numbers suggest. We tra

RULER: Instance-aware Rubric Rewards for SVG Generation

arXiv:2609.25270v1 Announce Type: new Abstract: Generating Scalable Vector Graphics (SVG) code from natural-language instructions is an open-ended task without absolute visual ground truth, leaving bo

SAM-V: Geometry-Aware Segment Anything for Multi-View Instance Segmentation

arXiv:2609.25490v1 Announce Type: cross Abstract: Consistent multi-view object segmentation is critical for 3D perception and robotics, yet remains challenging under severe viewpoint and occlusion cha

Same Quantity, Different Answer: Numerical Representation Invariance in Language Models

arXiv:2609.25009v1 Announce Type: new Abstract: Numerically equivalent word problems should yield the same canonical answer whether a quantity is written as a decimal, fraction, percentage, number wor

SAMI3D-DW: Interactive Segmentation of Any 3D Medical Images

arXiv:2609.25743v1 Announce Type: new Abstract: Interactive segmentation of 3D medical images supports quantitative analysis of anatomical structures and disease while allowing users to specify and re

SBMVTrack: Spike-Budgeted Multi-View Learning for Energy-Efficient UAV Tracking

arXiv:2609.25503v1 Announce Type: new Abstract: With sparse and event-driven computation, spiking neural networks show great potential for achieving accurate and energy-efficient UAV visual tracking.

Scalable Minimum-Volume Simplex Estimation with Non-asymptotic Analysis

arXiv:2609.25576v1 Announce Type: cross Abstract: We study the estimation of a K-dimensional simplex from N i.i.d. points sampled uniformly from its interior; the observations are convex combinations

SelfOp: An Optimization Algorithm for Self-Improving Security Agents

model-releasesarxiv-cs-ai

arXiv:2609.22792v1 Announce Type: cross Abstract: LLM agents are increasingly used for security tasks: vulnerability discovery, exploit reproduction, and patch generation. Improving them at the model

Semantically-Guided Domain Randomization for Industrial Object Detection in Low-Image-Budget Regimes

arXiv:2609.26505v1 Announce Type: new Abstract: Retraining visual perception pipelines in High-Mix, Low-Volume (HMLV) automotive manufacturing must be carried out under tight annotation, energy, and t

Separators in Enhancing Autoregressive Pretraining for Vision Mamba

arXiv:2603.03806v2 Announce Type: replace Abstract: The state space model Mamba has recently emerged as a promising paradigm in computer vision, attracting considerable attention for its efficient han

Sometimes You Gotta Run Before You Can Walk: Run-then-Walk Scheduling Strategy for VLM Autonomous Driving

arXiv:2609.25831v1 Announce Type: new Abstract: Recent VLM-based autonomous driving planners adopt GRPO-style reinforcement learning to optimize driving performance. However, existing GRPO recipes eit

safetyarxiv-cs-ro

SpeakerMem-R1: Speaker-Centered Dual-Track Memory for Multi-Party Dialogue

arXiv:2609.26780v1 Announce Type: new Abstract: Long-term conversational memory in multi-party settings requires more than retrieving relevant content from long-term conversations: it must distinguish

local-aiarxiv-cs-cl

SPEANet: Structural Prior Enhanced Attention Network for Parameter-Efficient Remote Sensing Object Detection

arXiv:2609.26064v1 Announce Type: new Abstract: Remote sensing object detection (RSOD) requires compact backbones capable of preserving weak geometric cues under extreme scale variation and background