Search: “benchmark”

arXiv:2603.16448v3 Announce Type: replace Abstract: Text-to-SQL parsing has achieved remarkable progress under the Full Schema Assumption. However, this premise fails in real-world enterprise environm

agentsarxiv-cs-ai

12 Sept 2026

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Model Releases

Verification of Adaptive Agentic Controllers through Finite Rule Revision

DGX agent

arXiv:2607.09770v2 Announce Type: replace Abstract: Industrial agentic AI systems increasingly exhibit a gap between prototype capability and production deployment. In particular, adaptive agents may

model-releasesarxiv-cs-ai

12 Sept 2026

3D Euler-Angle Orientation Control for Two-Ray Fading Mitigation in Maritime Air-to-Sea Communications

model-releasesarxiv-cs-ro

arXiv:2609.11476v1 Announce Type: new Abstract: Maritime Air-to-Sea links are dominated by a line-of-sight ray and a sea-surface reflected ray whose destructive combination produces deep fades. Existi

Applications

A Dataset and Model for Imputing Water Surface Elevation on a Large and Extremely Sparse Spatiotemporal Graph

arXiv:2609.11580v1 Announce Type: new Abstract: Continuous monitoring of water surface elevation across river networks is critical for flood forecasting, water resource management, and understanding t

applicationsarxiv-cs-lg

AdamX: Cosine similarity meets gradient descent

arXiv:2609.11867v1 Announce Type: new Abstract: We introduce AdamX, a first-order optimizer that incorporates cosine similarity as an adaptive mechanism for controlling update magnitudes. The proposed

Adaptive Margin Ordinal Loss: Penalizing Center-Class Hedging in Ordinal Classification

arXiv:2609.10752v1 Announce Type: new Abstract: Standard cross-entropy loss causes neural networks trained on ordinal classification tasks to hedge predictions toward center classes, a failure mode we

researcharxiv-cs-lg

Agents

Agents API is a bigger deal than it seems. OpenAI's bet on making the Codex harness open-source could pay off big time here. This harness-as…

Agents API is a bigger deal than it seems. OpenAI's bet on making the Codex harness open-source could pay off big time here. This harness-as-a-service idea hasn't hit mainstream yet, but some of the m

agentsdair-ai--x

Are frontier models actually becoming less important?

I’m genuinely mind-blown by what’s happening with AI models right now. On one side, you have GPT-6-class frontier models that are just… insane. The level of capability is getting hard to wrap your hea

model-releasesr-ollama

Breaking the Central Bias: Spatially Partitioned Experts for Coordinate-Based Neuroevolution

arXiv:2609.11518v1 Announce Type: cross Abstract: Evolvable-Substrate HyperNEAT (ES-HyperNEAT), a bio-inspired indirect encoding that determines neuron placement and connection weights from spatial co

Hardware

Building py-kvcache: A Performance Characterization of External KV Caching for vLLM with NVMe SSDs

arXiv:2609.11744v1 Announce Type: cross Abstract: Prefix caching can reduce the time to first token (TTFT) of long-context LLM requests by reusing previously computed key-value (KV) states, but for sh

hardwarearxiv-cs-lg

Building Supervision into Hebbian Plasticity through Spike Agreement

arXiv:2601.08526v2 Announce Type: replace-cross Abstract: Supervised learning in spiking neural networks (SNNs) typically requires either gradient-based backpropagation, which sacrifices the Hebbian,

CamPilot: A Multi-Agent Cinematic Assistant for Camera-Controlled Movie Generation

arXiv:2609.10943v1 Announce Type: new Abstract: The integration of large language models (LLMs) into video generation has enabled rapid text-to-video creation and improved visual quality. However, it

Agents

Caption-once, Frames-on-Demand: Visual-Need Routing for Budget-Aware Agentic Long Video Understanding

arXiv:2609.11899v1 Announce Type: new Abstract: Long-video understanding on edge devices must reason over hours of content under tight compute and bandwidth budgets. Subsampling visual tokens loses te

agentsarxiv-cs-cv

CertDW: Towards Certified Dataset Ownership Verification via Conformal Calibration

arXiv:2506.13160v2 Announce Type: replace-cross Abstract: Deep neural networks (DNNs) rely heavily on high-quality open-source datasets (e.g., ImageNet) for their success, making dataset ownership ver

Safety

Chess, go, and math are highly constrained, purely cognitive that allow exact simulation for games (and formal verification for math), and n…

Chess, go, and math are highly constrained, purely cognitive that allow exact simulation for games (and formal verification for math), and not in the open-ended physical world. As I have been arguing

safetygary-marcus--x

Convex Optimization with Nested Evolving Feasible Sets (CONES) under Time-Varying Loss Functions

arXiv:2609.11207v1 Announce Type: new Abstract: Convex Optimization with Nested Evolving Feasible Sets (CONES)} was introduced in ite{CONESVaze} where the objective function (f) remains fixed but the

Safety

Do Agents Know When They Succeed? Calibrating Agent Confidence from Internal Representations

arXiv:2609.09448v1 Announce Type: new Abstract: As agentic systems getting adopted rapidly in safety critical applications, it is vital to measure the confidence associated with the agentic actions. I

safetyarxiv-cs-ai

Domain Elastic Transform: Bayesian Function Registration for High-Dimensional Scientific Data

arXiv:2603.21235v2 Announce Type: replace-cross Abstract: Nonrigid registration is conventionally divided into point set registration, which aligns sparse geometries, and image registration, which ali

Emergency Department Revisit Quality Review Screening: Exploring Human Decision-Making and Artificial Intelligence Support

arXiv:2609.10421v1 Announce Type: cross Abstract: Background: Emergency Department (ED) return visits are commonly reviewed for quality assurance, but are often limited (e.g., to revisits within 48-72

EMMI: Edge Multi-Modal Intelligence for Communication-Efficient MLLM Inference via Fused Representation Compression

arXiv:2609.11058v1 Announce Type: new Abstract: Recent advances in multimodal large language mod- els (MLLMs) have opened new opportunities for edge intelligence by enabling reasoning across heterogen

Empirical Evaluation of Membership Inference Attacks on NLP Text Classifiers: A Baseline Study on SST-2

model-releasesarxiv-cs-cl

arXiv:2609.10935v1 Announce Type: cross Abstract: Membership inference attacks (MIAs) try to determine whether a specific record was used to train a model, a privacy risk that matters in natural langu

Local Ai

Exponential Pixelating Integral transform with dual fractal features for enhanced chest X-ray abnormality detection

arXiv:2609.10988v1 Announce Type: cross Abstract: The heightened prevalence of respiratory disorders, particularly exacerbated by a significant upswing in fatalities due to the novel coronavirus, unde

local-aiarxiv-cs-cv

FARM: Reading Failure Signals from the Internal Predictive States of a Frozen Robotic World Model

model-releasesarxiv-cs-ro

arXiv:2609.11445v1 Announce Type: new Abstract: Reliable robot deployment requires online failure monitoring, yet existing monitors mainly derive risk from proxy signals or train dedicated monitoring

FastMap: Real-Time Semantic Map Completion via Bitwise Masked Modeling

arXiv:2506.07350v2 Announce Type: replace-cross Abstract: Semantic map completion, which predicts the layout of unobserved regions from partial observations, is a critical capability for indoor robot

Local Ai

FreeFlow: A Bias-free Hierarchical Transformer for Optical Flow Estimation

arXiv:2609.11486v1 Announce Type: new Abstract: Optical flow methods typically rely on task-specific inductive biases, such as correlation volumes, feature warping, and iterative refinement, among oth

local-aiarxiv-cs-cv

From Cycle Space to Cycle Manifold: Limits and Achievability of Blind False Data Injection Attacks

arXiv:2609.10631v1 Announce Type: cross Abstract: A false data injection attack (FDIA) can change the estimated grid state while evading a residual-based bad data detector (BDD). Existing blind attack

Fugu Max pushes the Pareto Frontier for price-performance: • 2 input / 6 output per 1M tokens. • Performance within striking distance of e…

Fugu Max pushes the Pareto Frontier for price-performance: • 2 input / 6 output per 1M tokens. • Performance within striking distance of elite models at 2x to 6x lower cost. • Best overall score on 6

researchdavid-ha--x

Generative AI for Analysts

arXiv:2512.19705v2 Announce Type: replace-cross Abstract: We study how generative artificial intelligence (GenAI) reshapes financial analysts' information production. Using the 2023 integration of Gen

Local Ai

Generative Replay Mitigates Sample Starvation in Quantum Architecture Search

arXiv:2609.11248v1 Announce Type: cross Abstract: Reinforcement learning (RL) can automate quantum architecture search, but its scalability is limited when useful circuit trajectories become rare in t

local-aiarxiv-cs-lg

Tutorials

GEOSTEER: Geodesic Optimization for Activation Steering in Large Language Models

arXiv:2609.10658v1 Announce Type: new Abstract: Activation steering provides a lightweight way to control large language models (LLMs) by modifying their hidden activations at inference time. Among th

tutorialsarxiv-cs-lg

GRIPNet: Gaussian Radial Intensity Prior Guided Architecture for Pulmonary Nodule Detection in CT

arXiv:2609.11312v1 Announce Type: new Abstract: Lung cancer causes more deaths than any other malignancy, and low-dose CT screening is the main pathway to early diagnosis. That pathway hinges on the s

researcharxiv-cs-cv

Halo: Improving forecast accuracy through heteroscedastic estimation

arXiv:2609.10589v1 Announce Type: new Abstract: Heteroscedastic forecasting, where a network estimates a scale parameter alongside a location parameter, is normally motivated by uncertainty quantifica

Harnessing Intrinsic Subject-Aware Attention for Controllable Multi-Subject Video Generation

arXiv:2609.11507v1 Announce Type: new Abstract: Multi-subject video generation faces two key challenges: uncontrollable fidelity strength and potential semantic drift. We address these by analyzing th

HERALD: High-Fidelity Exemplar Retrieval with Adaptive Landmark Distillation for Heterophily-Aware Graph Condensation

arXiv:2609.11123v1 Announce Type: new Abstract: Graph condensation aims to produce a small surrogate graph that preserves the downstream node-classification performance of a much larger original graph

HISA: Efficient Hierarchical Indexing for Fine-Grained Sparse Attention

arXiv:2603.28458v4 Announce Type: replace Abstract: Token-level sparse attention mechanisms, exemplified by DeepSeek Sparse Attention (DSA), achieve fine-grained key selection by scoring every histori

IMLE-VLA: Fast Single-Step Action Generation for Vision-Language-Action Policies

arXiv:2609.10915v1 Announce Type: cross Abstract: Vision-language-action (VLA) policies leverage pretrained vision-language backbones to achieve strong cross-task generalization. A leading design coup

Improving 5G AI-RAN MCS Selection by Predicting Retransmissions

arXiv:2609.09324v1 Announce Type: cross Abstract: Link Adaptation (LA) in 5G NR is inherently reactive, relying on channel measurements and HARQ feedback that may become quickly obsolete when the chan

IndicTriMix: Developing Language Identification Datasets and Models for Tri-Language Code-Mixing

model-releasesarxiv-cs-cl

arXiv:2609.11851v1 Announce Type: new Abstract: Language identification in code-mixed text, largely observed in social media, is highly essential when users frequently switch between multiple language

Introducing Fugu Max and Fugu Ultra v2: the next evolution of Sakana Fugu’s multi-agent orchestration system. Try: https://sakana.ai/fugu Bl…

model-releasesdavid-ha--x

Introducing Fugu Max and Fugu Ultra v2: the next evolution of Sakana Fugu’s multi-agent orchestration system. Try: https://sakana.ai/fugu Blog: https://sakana.ai/fugu-max-release/ The frontier that ac

LangStreet: Persistent Language Fields for Anchor-Decoded Street Gaussians

arXiv:2609.11616v1 Announce Type: new Abstract: Language Gaussian fields implicitly assume that the primitive carrying semantics remains identifiable across views. This assumption breaks in scalable a

llama.cpp ngram on RAM/SSD?

model-releasesr-localllama

I've been out of the loop for some time. Is there already an official way to offload ngram to RAM or SSD in something like Unsloth Studio? Interested in running Qwen3.8-Flash-Next on 72GB VRAM, but na

Local Robustness Quantification for Naive Bayes Classifiers and Generative Forests: a General Approach

arXiv:2609.11366v1 Announce Type: new Abstract: We provide methods for calculating the robustness of the predictions of two types of generative classifiers whose underlying distribution is a Probabili

MisEdu-RAG: A Misconception-Aware Dual-Hypergraph RAG for Novice Math Teachers

model-releasesarxiv-cs-cl

arXiv:2604.04036v2 Announce Type: replace-cross Abstract: Novice math teachers often encounter students' mistakes that are difficult to diagnose and remediate. Misconceptions are especially challengin

Multi-Agent Agentic Graph Learning via Structural Signatures

arXiv:2609.09565v1 Announce Type: new Abstract: Agentic graph learning (AGL) has recently achieved promising results on graph reasoning tasks, where an agent powered by a large language model (LLM) se

Multi-Modal Controlled Coherent Motion Generation

arXiv:2609.11439v1 Announce Type: new Abstract: It is natural for humans to walk and talk simultaneously. This paper tackles the challenge of replicating such natural behaviors in 3D avatar motion gen

OmniKVQuant: KV Cache Quantization for Omni-LLMs

arXiv:2609.11582v1 Announce Type: new Abstract: As Omni-modal large language models (Omni-LLMs) take in audio, video and text together, their KV cache memory cost grows. KV cache quantization is the d

researcharxiv-cs-cv

On the Impact of Anonymization on the Performance of Large Language Models

arXiv:2609.11335v1 Announce Type: new Abstract: As large language models are increasingly deployed in sensitive domains, anonymizing input data to protect personally identifiable information has becom

researcharxiv-cs-cl

Applications

Optimizing Three Critical Factors for Practical and Effective OOD Detection Fine-Tuning

arXiv:2308.01030v2 Announce Type: replace-cross Abstract: In out-of-distribution (OOD) detection, fine-tuning with auxiliary outlier data often improves detection performance at the cost of classifica

applicationsarxiv-cs-cv