Search: “benchmark”

How SWE-Serve Exposes the Gap Between Local Tests and Live Serving

SWE‑Serve evaluates AI coding agents on 53 inference‑engineering tasks derived from SGLang pull requests across six functional domains. Among 19 tasks that launch a live server, patches that pass loca

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Agents

ICDAR2026 Competition on Multimodal Reasoning over Documents in Multiple Domains

DGX agent

arXiv:2609.25055v1 Announce Type: new Abstract: In this report we present results of the ICDAR2026 Competition on Multimodal Reasoning over Documents in Multiple Domains. This competition aimed to adv

agentsarxiv-cs-cl

23 Sept 2026

Tutorials

In-Context Guidance: Learning Inter-Task Synergies via Numerical Foundational Models for Few-Shot Multitask Optimization

arXiv:2609.25836v1 Announce Type: new Abstract: Multi-task optimization (MTO) addresses a set of optimization tasks simultaneously, often suffering from inaccurate inter-task relationship estimation u

tutorialsarxiv-cs-lg

Information-Theoretic Decoupled Prompt Tuning for Continual Learning

arXiv:2609.26257v1 Announce Type: new Abstract: Continual learning (CL) aims to incrementally acquire knowledge from sequential data while avoiding catastrophic forgetting. Recently, prompt tuning has

safetyarxiv-cs-lg

Informed Masking: Structure-Aware Perturbation for Reinforcement Learning in Diffusion Large Language Models

arXiv:2609.25927v1 Announce Type: new Abstract: Diffusion Large Language Models (dLLMs) have emerged as an efficient alternative to autoregressive models, yet aligning them via Reinforcement Learning

local-aiarxiv-cs-cl

Hardware

Interesting paper on agent memory stored as a linked markdown wiki. Lots of great ideas and insights if you work with LLM Wikis. Wikis are u…

Interesting paper on agent memory stored as a linked markdown wiki. Lots of great ideas and insights if you work with LLM Wikis. Wikis are useful for agents because each page holds dense text and the

hardwaredair-ai--x

Agents

Introducing Contrastive Language Model (CLM): an ultra-fast System One Model trained with a contrastive learning objective that connects sta…

Introducing Contrastive Language Model (CLM): an ultra-fast System One Model trained with a contrastive learning objective that connects states and actions. CLM-8B is pre-trained on internet-scale dat

agentsyohei-nakajima--x

Hardware

Introducing NV-Reason-CT Open 3D CT VLM for Radiologist Chain-of-Thought Reasoning

NV‑Reason‑CT is a purpose‑built vision‑language model for volumetric CT that uses a full 3‑D Vision Transformer encoder coupled with a Qwen 3.5‑4B language model to generate radiologist‑style chain‑of

hardwarenvidia-developer

Applications

JAMPR+/L2D: scalable neural heuristic for constrained vehicle routing problems in dynamic environment

arXiv:2609.26275v1 Announce Type: new Abstract: The vehicle routing problems with real-world constraints (we consider vehicles capacity limits, time windows constrains, pickup-and-delivery multi-depo

applicationsarxiv-cs-lg

LADDER: Graph-Guided Diffusion Language Models for Efficient Multi-Hop Reasoning

arXiv:2609.24346v1 Announce Type: new Abstract: Graph Retrieval-Augmented Generation (GraphRAG) has remarkably enhanced large language models on complex reasoning by leveraging structured entity topol

safetyarxiv-cs-ai

Layout-Guided Masking for GROBID: Lightweight Structural Gains in Large-Scale Scientific PDF Ingestion

arXiv:2609.26381v1 Announce Type: new Abstract: Transforming scholarly PDFs into machine-readable fulltext remains a bottleneck for large-scale information systems. Recent vision-based parsers improve

LEAP-NBV: Lightweight Edge Active-Perception for Foundation-Model Next-Best-View Planning

model-releasesarxiv-cs-ai

arXiv:2609.23974v1 Announce Type: new Abstract: Foundation models are endowing autonomous systems with greater intelligence, enabling a more comprehensive understanding of the environment through visu

LIMIT: Less Is More for Instruction Tuning in Text-to-SQL

model-releasesarxiv-cs-ai

arXiv:2609.24186v1 Announce Type: new Abstract: Large language models have achieved remarkable progress on Text-to-SQL through reasoning-enhanced fine-tuning, yet existing approaches predominantly rel

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

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

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

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

New paper! 🫡 We introduce Matryoshka Attribution, a new attribution method which uses gradient descent to find which parts of a neural netw…

model-releasesyohei-nakajima--x

New paper! 🫡 We introduce Matryoshka Attribution, a new attribution method which uses gradient descent to find which parts of a neural network are responsible for a behaviour. MAttr is #1 on the Mecha

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

Qwen FN vs 27B --- Think I'm saturated.

model-releasesr-localllama

Got QFN up and running on our Strix box this past weekend and have been running on it for a few days now. Big thank you/shout out to the Halogen team, it's running fantastic on the Strix, this is clea

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