Search: “benchmark”

FillGS: Filling Observation Gaps in 4D Gaussian Splatting via Viewpoint-Time Selection and Generative Refinement

arXiv:2607.29284v1 Announce Type: new Abstract: 4D Gaussian Splatting (4DGS) can render dynamic scenes photorealistically. However, with limited viewpoint coverage, some spatiotemporal regions remain

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FineInstructions: Scaling Synthetic Instructions to Pre-Training Scale

DGX agent

arXiv:2601.22146v3 Announce Type: replace Abstract: Due to limited supervised training data, large language models (LLMs) are typically pre-trained via a self-supervised 'predict the next word' object

researcharxiv-cs-cl

3 Aug 2026

GEMSS: A Variational Method for Discovering Multiple Sparse Solutions in Classification and Regression Problems

arXiv:2602.08913v3 Announce Type: replace Abstract: In underdetermined regression and classification problems, multiple feature subsets often yield equivalent predictive performance. In applied settin

GoldenRetriever: Non-Interactive Homomorphic Encrypted Retrieval for Privacy-Preserving RAG

arXiv:2607.29019v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) enhances large language models by incorporating external knowledge, but existing pipelines typically operate on p

researcharxiv-cs-cl

HarnessBank: Semantic Gene-Bank Search with Gated Verification for Agent-Harness Self-Evolution

arXiv:2607.13683v2 Announce Type: replace Abstract: Large Language Models (LLMs) have enabled capable agents across diverse applications. Beyond the foundation model, the performance of an agent is go

agentsarxiv-cs-cl

HERO: History-Enriched Rollout Training for Long-Horizon Autoregressive Neural Operators

arXiv:2607.29135v1 Announce Type: cross Abstract: Neural operators provide fast surrogates for time-dependent partial differential equations (PDEs) by applying a learned evolution operator recursively

local-aiarxiv-cs-ai

HierDoc: Hierarchical Page-to-Region Evidence Routing for Long-Document Visual Question Answering

arXiv:2607.29638v1 Announce Type: new Abstract: Multi-page document visual question answering requires locating sparse evidence at both the page and region levels. Existing approaches typically emphas

safetyarxiv-cs-cv

How Hard Does It Think? Analyzing Step-Aware Reasoning Energy in LLM Chain-of-Thought Trajectories

arXiv:2607.28674v1 Announce Type: new Abstract: Understanding how computational effort is allocated across individual chain-of-thought (CoT) reasoning steps remains an open challenge: existing interpr

safetyarxiv-cs-ai

I compared MinerU, Granite-Docling, and PaddleOCR-VL on 12 PDF-parsing capabilities using 6 document types

I tested them by sending the 6 documents, each meant to represent a different document type, through my own webapp and comparing every output against the source. All ran on the same L4 GPU. The docume

Identifying Informative Environments for Cognition Parameter Inference via Bayesian Experimental Design

arXiv:2607.28894v1 Announce Type: new Abstract: Computational cognitive modeling seeks to infer latent cognitive mechanisms underlying observed behavior. Bayesian inverse planning provides a principle

KAT Coder 2.5 dev: Do yourself a favor and try it!

It is so good! I don't know why there aren't more people talking about it. Fewer tokens, faster and more accurate than Qwen 3.6 35b a3b. On my setup it's nearly as good as 27b, but 5x faster. And it c

Knowledge Restoration-driven Prompt Optimization: Unlocking LLM Potential for Open-Domain Relational Triplet Extraction

arXiv:2601.15037v2 Announce Type: replace-cross Abstract: Open-domain Relational Triplet Extraction (ORTE) aims to mine structured knowledge without predefined relation schemas. Large Language Models

researcharxiv-cs-ai

Latent Sculpting for Zero-Shot Generalization: A Manifold Learning Approach to Out-of-Distribution Anomaly Detection

arXiv:2512.22179v3 Announce Type: replace Abstract: Detecting previously unseen attacks remains a major challenge for machine learning-based intrusion detection systems. Deep models trained on network

LEMUR: Learning to Align with Multi-Objective Reinforcement Learning from Preference Feedback

arXiv:2607.29559v1 Announce Type: new Abstract: Reinforcement Learning (RL) systems are typically trained using a single, well-specified scalar reward function. However, real-world decision-making tas

LightningRL: Breaking the Accuracy-Parallelism Trade-off of Block-wise dLLMs via Reinforcement Learning

arXiv:2603.13319v2 Announce Type: replace Abstract: Diffusion Large Language Models (dLLMs) have emerged as a promising paradigm for parallel token generation, with block-wise variants garnering signi

local-aiarxiv-cs-lg

Locally Consistent Transductive Information Maximization for Few-Shot Remote Sensing Scene Classification

arXiv:2607.29192v1 Announce Type: new Abstract: Remote sensing scene classification is increasingly relying on foundation models pre-trained on large-scale Earth-observation data. Moreover, transducti

MHRGait: Gait Recognition from Momentum Human Rig Pose

arXiv:2607.29083v1 Announce Type: new Abstract: Gait recognition is shaped by its input representation. Silhouettes encode projected body shape, skeletons encode sparse joint coordinates, and 3D meshe

Mining Verdict Boundaries for Neural Network Verification

arXiv:2607.28954v1 Announce Type: new Abstract: Branch and Bound (BaB) aims to achieve complete verification of neural networks by adaptively partitioning the problem and applying off-the-shelf verifi

researcharxiv-cs-lg

MoPET: Parameter-Efficient Mixture-of-Experts for Unified Medical Image Classification

arXiv:2607.29462v1 Announce Type: cross Abstract: Adapting deep learning models to profound clinical heterogeneity typically relies on parameter-efficient fine-tuning (PEFT) to avoid the severe overfi

MoRoute: Dynamic Routing for In-Context Multimodal Video Generation

arXiv:2607.29545v1 Announce Type: new Abstract: Multimodal video generation aims to generate and edit videos conditioned on arbitrary combinations of text, images, and videos within a single model, al

Multi-Modal Object Re-Identification with Dual Semantic Guidance and Global-Local Mutual Modulation

arXiv:2607.29207v1 Announce Type: new Abstract: Multi-modal object Re-Identification (ReID) aims to retrieve target instances by leveraging complementary information across modalities. However, existi

safetyarxiv-cs-cv

Multimodal Reinforcement Learning with Adaptive Verifier for AI Agents

arXiv:2512.03438v3 Announce Type: replace Abstract: Agentic reasoning models trained with multimodal reinforcement learning (MMRL) have become increasingly capable, yet they are almost universally opt

local-aiarxiv-cs-ai

NeSyFS: A Neuro-symbolic Fast-Slow Thinking Framework for LLM Agent under Partial Observability

arXiv:2607.28942v1 Announce Type: new Abstract: Recently Large Language Models (LLMs) have been increasingly deployed as autonomous agents in applications such as self-reflection, retrieval-augmented

agentsarxiv-cs-ai

[NEW MODELS!] Supra2-100M Base and Instruct - go check them out!

Hey guys! After a LOT of good feedback on our previous models like Supra-50M-Instruct and -Reasoning, many community likes, follows and upvotes we saw many community requests asking for new models. We

local-air-localllama

'Not in My Backyard': LLMs Uncover Online and Offline Social Biases Against Homelessness

arXiv:2508.13187v5 Announce Type: replace-cross Abstract: Homelessness is a persistent social challenge, impacting millions worldwide. Over 876,000 people experiencing homelessness (PEH) were recorded

On the Expressive Power of Sparse Geometric MPNNs

arXiv:2407.02025v5 Announce Type: replace-cross Abstract: Motivated by applications in chemistry and other sciences, we study the expressive power of message-passing neural networks for geometric grap

researcharxiv-cs-ai

Open-Source LLM-Driven Formal Verification: A Multi-Agent Pipeline for RTL Repair

arXiv:2607.28877v1 Announce Type: cross Abstract: Verification consumes the majority of modern chip design effort, yet the formal verification tools that provide mathematical guarantees of correctness

Outcome-Guided Distillation: A Teacher-Student Framework to Advance VLM Reasoning in Autonomous Driving

arXiv:2607.29052v1 Announce Type: new Abstract: End-to-end (E2E) autonomous driving aims to learn a direct mapping from visual observations to control actions. However, these E2E models often act as b

agentsarxiv-cs-ro

Parameter-Efficient Fine-Tuning for Spiking Point Cloud Models

arXiv:2607.29048v1 Announce Type: new Abstract: Spiking Neural Networks (SNNs) offer energy-efficient solutions for point cloud analysis on resource-constrained devices through event-driven computatio

PhyUnfold-Net: Advancing Remote Sensing Change Detection with Physics-Guided Deep Unfolding

arXiv:2603.19566v3 Announce Type: replace Abstract: Bi-temporal change detection is highly sensitive to acquisition discrepancies, including illumination, season, and atmosphere, which often cause fal

PluRel-to-RDB-PFN: Schema-Guided Synthetic Relational Pretraining

arXiv:2607.29129v1 Announce Type: new Abstract: Relational Foundation Models (RFMs) require large-scale synthetic relational databases for pretraining, but existing approaches tightly couple data gene

POSSE-kNN: Pathwise Out-of-Bag Selected Subspace Ensembles for Binary Classification

arXiv:2211.11278v3 Announce Type: replace-cross Abstract: Nearest neighbour classification is attractive for tabular data, but its performance can deteriorate when a fixed query centred neighbourhood

Predicting Steel Fatigue Life from Micrographs Using Physics-Informed Deep Learning

arXiv:2607.28695v1 Announce Type: cross Abstract: Here is the plain text version optimized for arXiv's submission form. Custom macros (like CV and SI) have been converted to standard text/math so they

Progressive Decision-Making for Localizing Open-Ended AI-Generated Image Forgeries

arXiv:2607.29156v1 Announce Type: new Abstract: AI-generated image forgeries are becoming increasingly realistic and difficult to characterize with fixed manipulation patterns. As generative models co

local-aiarxiv-cs-cv

Question about Quant versus Size.

Sorry if this is asked a lot, but I was wondering if there is any clear winner on the Quantization versus Model Size debate? I can run Qwen3.6 27b at Q8, Laguna at Q6, and the new Deepseek Flash at Q3

RAID: Towards Robust AI-Generated Image Detection with Bit-Reversed Images

arXiv:2607.28974v1 Announce Type: cross Abstract: The rapid advancement of image generation models has made it increasingly difficult for people to distinguish AI-generated images from real ones. To p

researcharxiv-cs-ai

RareSense: Rarity-Aware Similarity Search for Anomaly Retrieval in Transactional Data

arXiv:2607.28879v1 Announce Type: cross Abstract: Similarity search over sparse set-valued data is often dominated by frequent background attributes because classical measures such as Jaccard, cosine,

RayViT: Ray-Conditioned Visual Representations for Viewpoint-Robust Imitation Learning

arXiv:2607.29622v1 Announce Type: cross Abstract: Visual imitation learning enables robots to acquire visuomotor skills directly from images, yet RGB observations lack explicit geometric cues, making

Receding-Horizon Next-Best-View Planner for Autonomous Leaf Surface Reconstruction

model-releasesarxiv-cs-ro

arXiv:2607.28995v1 Announce Type: new Abstract: Accurate plant leaf modeling is fundamental to downstream tasks such as plant growth monitoring, and phenotyping for yield estimation. Autonomous roboti

Reflected UAS: Corrected Deterministic Stability and Direct CTMC Drift Calculation

arXiv:2607.28688v1 Announce Type: cross Abstract: We analyze Reflected UAS routing for heterogeneous multi-server queues at fixed parameters under subcritical load. The deterministic surrogate is a re

[RELEASE] SupraBrain-50M-v0.1

Hey there! So today we're releasing SupraBrain-50M, a hybrid language model that combines Gated DeltaNet linear recurrence with Sliding-Window Attention and Surprise-Gated update mechanisms to deliver

Role-Break in Attention Heads: Understanding and Detecting Hallucinations in VLMs

arXiv:2607.29412v1 Announce Type: new Abstract: Despite remarkable progress in vision-language generation, Vision-Language Models (VLMs) remain prone to hallucinations, producing content that is incon

SAF-OPD: Stable Advantage Fusion for On-Policy Distillation

arXiv:2607.29209v1 Announce Type: cross Abstract: Reinforcement learning with verifiable rewards (RLVR) broadcasts a single response-level reward to every token, while on-policy distillation (OPD) sco

safetyarxiv-cs-ai

Safe Vision Language Action Models via Barrier Enhanced Flow Matching

model-releasesarxiv-cs-ro

arXiv:2607.29569v1 Announce Type: new Abstract: This article presents a modular inference framework that integrates Flow Matching generative models with formal Control Barrier Function (CBF) safety gu

SafeNexus: Discovering and Steering Modality-Universal Safety Neurons in MLLMs

arXiv:2607.28969v1 Announce Type: new Abstract: Although Large Language Models (LLMs) have demonstrated promising safety performance, extending them to Multimodal Large Language Models (MLLMs) exposes

local-aiarxiv-cs-cv

SAM+D: Parameter-Efficient Dimensional Lifting of SAM-Family Models via Depth-Routed LoRA and Depth Shifting

arXiv:2607.29033v1 Announce Type: new Abstract: Existing methods for adapting 2D foundation models such as SAM to 3D volumes either process slices independently---ignoring inter-slice context---or req

Scaling Properties of Text Conditioning in Visual Generation

arXiv:2607.29679v1 Announce Type: new Abstract: We study empirical scaling properties for text conditioning in visual generation. Such properties have rarely been measured because diffusion loss does

Scaling Scientific Discovery Environments for Turn-Level Agentic RL

arXiv:2607.28990v1 Announce Type: new Abstract: Large language model agents have shown promising capabilities in data-driven scientific discovery tasks, where an agent interacts with an execution envi

agentsarxiv-cs-ai