Search: “benchmark”

DR-Arena: an Automated Evaluation Framework for Deep Research Agents

arXiv:2601.10504v2 Announce Type: replace Abstract: As Large Language Models (LLMs) increasingly operate as Deep Research (DR) Agents capable of autonomous investigation and information synthesis, rel

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Dual-Difficulty Curriculum Learning for Direct Preference Optimization

DGX agent

arXiv:2504.07856v4 Announce Type: replace Abstract: Curriculum learning enhances Direct Preference Optimization (DPO) for aligning Large Language Models (LLMs), yet existing methods rely on a one-dime

safetyarxiv-cs-ai

10 Jul 2026

Echoes Across Vietnam's Highlands, Delta, and Coast: A Multilingual Corpus for Cham, Khmer, and Tay-Nung

model-releasesarxiv-cs-cl

arXiv:2607.08362v1 Announce Type: new Abstract: Vietnam's ethnic minority languages are almost absent from the field of Natural Language Processing (NLP), and the challenge goes beyond data scarcity:

Efficient Safety Alignment of Language Models via Latent Personality Traits

arXiv:2607.07918v1 Announce Type: cross Abstract: Current safety methods for large language models are known to be vulnerable to adversarial attacks, motivating research into robust alternatives. Late

safetyarxiv-cs-ai

Ensemble Diversity Optimization for Subjective Supervision

arXiv:2607.08493v1 Announce Type: cross Abstract: Subjective NLP tasks often exhibit systematic annotator disagreement, requiring models that represent uncertainty rather than collapse it. We introduc

Equivariant Quantum Clustering with Differential Privacy: Parameter-Efficient Privacy-Preserving Analysis Across Heterogeneous Sensitive Datasets

arXiv:2607.08092v1 Announce Type: cross Abstract: Privacy-preserving clustering is critical for analyzing sensitive data in healthcare, cybersecurity, and enterprise applications, where maintaining da

FabriVLA: A Lightweight Vision-Language-Action Model for Precise Multi-Task Manipulation

model-releasesarxiv-cs-ro

arXiv:2607.08575v1 Announce Type: new Abstract: We present FabriVLA, a lightweight Vision-Language-Action model for Precise Multi-Task Manipulation. FabriVLA combines an InternVL3.5 vision-language ba

FedOPAL: One-Shot Federated Learning via Analytic Visual Prompt Tuning

arXiv:2607.08368v1 Announce Type: new Abstract: With the widespread deployment of basic models in edge intelligence, communication bandwidth has become a core bottleneck restricting the scalability of

Applications

From Execution to Education: A Bloom-Aligned Framework for Measuring Educational Control in LLMs

arXiv:2607.08009v1 Announce Type: new Abstract: We introduce a Bloom-aligned framework for measuring educational control in Large Language Models (LLMs): the ability to preserve a task's instructional

applicationsarxiv-cs-cl

Functional and Secure Code Generation with Task Vectors

model-releasesarxiv-cs-lg

arXiv:2607.07881v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used for code generation, but they struggle to generate functional code free of security vulnerabilities

Agents

Game Theory Driven Multi-Agent Framework Mitigates Language Model Hallucination

arXiv:2607.08403v1 Announce Type: new Abstract: The application of lightweight Large Language Models in rule-based scientific domains remains severely limited by their tendency to mimic linguistic pat

agentsarxiv-cs-ai

Geometry and Gradient-based Partitioning for Panoramic Outdoor Reconstruction

arXiv:2607.08769v1 Announce Type: new Abstract: Scaling 3D Gaussian Splatting (3DGS) to large outdoor scenes is costly in both data acquisition and computation. Adopting panoramic images with equirect

Geometry-Aware Deep Congruence Networks for Manifold Learning in Cross-Subject Motor Imagery

arXiv:2511.18940v3 Announce Type: replace Abstract: Cross-subject motor imagery decoding remains a fundamental challenge in EEG-based brain-computer interfaces due to substantial inter-subject variabi

safetyarxiv-cs-lg

Goal-Driven Reasoning in DatalogMTL with Magic Sets

arXiv:2412.07259v5 Announce Type: replace Abstract: DatalogMTL is a powerful rule-based language for temporal reasoning. Due to its high expressive power and flexible modeling capabilities, it is suit

Local Ai

Graph-Loc: Robust Graph-Based LiDAR Pose Tracking with Compact Structural Map Priors under Low Observability and Occlusion

arXiv:2602.08417v2 Announce Type: replace Abstract: Map-based LiDAR pose tracking is essential for long-term autonomous operation, where onboard map priors need be compact for scalable storage and fas

local-aiarxiv-cs-ro

Hallucination Self-Play: Bootstrapping Reinforced Detector via Evolved Generator

model-releasesarxiv-cs-cl

arXiv:2607.07993v1 Announce Type: new Abstract: Identifying faithfulness hallucinations in LLM-generated outputs remains challenging due to the scarcity of high-quality annotated data. Recent work rel

HeaPA: Difficulty-Aware Heap Sampling and On-Policy Query Augmentation for LLM Reinforcement Learning

arXiv:2601.22448v2 Announce Type: replace-cross Abstract: RLVR has become a standard recipe for training LLMs on reasoning tasks with verifiable outcomes, but when rollout generation dominates the cos

Hardware

Image classification via a quantum-inspired strategy involving a mixture of experts

arXiv:2607.07754v1 Announce Type: new Abstract: Pattern recognition problems arise in a variety of physical image processing situations, and convolutional neural networks are a popular scheme for the

hardwarearxiv-cs-lg

Jet-Long: Efficient Long-Context Extension with Dynamic Bifocal RoPE

arXiv:2607.07740v1 Announce Type: cross Abstract: Modern LLMs are increasingly deployed in long-context applications such as retrieval-augmented generation, repository-level coding, and agentic workfl

Joint Discrete-Continuous Flow Matching for Open-Vocabulary Inverse Design of Multilayer Optical Coatings

model-releasesarxiv-cs-lg

arXiv:2607.08392v1 Announce Type: cross Abstract: Amortized neural inverse design typically remains closed-world: component choices are fixed vocabulary tokens, coordinate grids are frozen at training

Learning Adaptive Solvers for Distributed Factor Graph Optimization on Matrix Lie Groups

arXiv:2607.08735v1 Announce Type: new Abstract: Modern robotic perception increasingly involves large-scale geometric optimization problems distributed across multiple robots or sessions. However, exi

safetyarxiv-cs-ro

Agents

LEEVLA: Seeing What Matters in Latent Environment Evolution for Vision-Language-Action

arXiv:2607.08182v1 Announce Type: cross Abstract: Vision-language-action (VLA) models aim to map multimodal inputs to robot actions. However, most existing approaches struggle to cover complex dynamic

agentsarxiv-cs-ai

Less Data, Faster Convergence: Goal-Driven Data Optimization for Multimodal Instruction Tuning

arXiv:2603.12478v2 Announce Type: replace Abstract: Multimodal instruction tuning is often compute-inefficient because training budgets are spread across large mixed image-video pools whose utility is

LESV: Language Embedded Sparse Voxel Fusion for Open-Vocabulary 3D Scene Understanding

arXiv:2604.01388v2 Announce Type: replace Abstract: Recent advancements in open-vocabulary 3D scene understanding heavily rely on 3D Gaussian Splatting (3DGS) to register vision-language features into

safetyarxiv-cs-cv

Linear Attention Architectures: Mechanisms, Trade-offs, and Cross-Layer Routing

arXiv:2607.07953v1 Announce Type: cross Abstract: Self-attention lets each token retrieve information from the full context, but its quadratic cost in sequence length limits training and inference at

LlamaSeg: Image Segmentation via Autoregressive Mask Generation

arXiv:2505.19422v2 Announce Type: replace Abstract: We present extbf{LlamaSeg}, a visual autoregressive framework that unifies multiple image segmentation tasks via natural language instructions. By r

LongE2V: Long-Horizon Event-based Video Reconstruction, Prediction, and Frame Interpolation with Video Diffusion Models

arXiv:2607.08770v1 Announce Type: new Abstract: Recovering high-quality video from sparse event streams is a challenging task. Regression methods often blur textures, while existing generative models

safetyarxiv-cs-cv

LUMI: Tokenizer-Agnostic LLM-Based Lossless Image Compression

arXiv:2607.08221v1 Announce Type: new Abstract: Large language model (LLM)-based lossless image compression methods typically represent pixel data through the native text interface of a pretrained mod

Mechanistic Interpretability of LLM Jailbreaks via Internal Attribution Graphs

arXiv:2607.07903v1 Announce Type: cross Abstract: Large language models (LLMs) exhibit remarkable capabilities but remain highly vulnerable to adversarial prompts and jailbreak attacks. Existing appro

safetyarxiv-cs-ai

MetaHGNIE: Meta-Path Induced Hypergraph Contrastive Learning in Heterogeneous Knowledge Graphs

arXiv:2512.12477v2 Announce Type: replace Abstract: Estimating node importance in heterogeneous knowledge graphs is a fundamental problem underlying recommendation, search, and knowledge decision syst

MSRNet: A Multi-Scale Recursive Network for Camouflaged Object Detection

arXiv:2511.12810v2 Announce Type: replace-cross Abstract: Camouflaged object detection is an emerging and challenging computer vision task that requires identifying and segmenting objects that blend s

Multimodal 3D LUT Generation via StatLUT with Statistical Features for Photorealistic Style Transfer

arXiv:2607.08227v1 Announce Type: new Abstract: Photorealistic Style Transfer (PST) aims to transfer the color and tonal style of a reference to a content image while strictly preserving its structura

researcharxiv-cs-cv

Open-Vocabulary Object-Goal Navigation by Generalizing Semantic Mapping with Dense CLIP

arXiv:2407.09016v2 Announce Type: replace Abstract: Object-oriented embodied navigation tasks require agents to locate specific objects, either defined by category or images, in unseen environments. W

researcharxiv-cs-ro

OpenCoF: Learning to Reason Through Video Generation

arXiv:2607.08763v1 Announce Type: cross Abstract: Reasoning has become a core capability for large models, especially when reliable decisions require understanding logical consequences. Recent video g

path_boost: A Python Package for Interpretable Graph-Level Prediction using Path-Based Gradient Boosting

arXiv:2607.07935v1 Announce Type: cross Abstract: We present path_boost, a Python package for interpretable supervised learning on graph-structured input data. The package implements PathBoost, a grad

Local Ai

PGD-NO: A Neural Operator with Precomputed Geometry Decomposition for 3D Million-scale Physics Simulations

arXiv:2607.08025v1 Announce Type: new Abstract: While neural PDE solvers have demonstrated significant potential for accelerating engineering simulations, existing architectures remain constrained by

local-aiarxiv-cs-lg

PIT-SUN: A Deployable Empirical Marginal Transform Framework with Expectation-Consistent Recovery for Regression in Recommender Systems

arXiv:2607.08202v1 Announce Type: new Abstract: Estimating original-space conditional expectations is central to value-driven recommender systems, including dwell time, GMV, and LTV forecasting. Stand

researcharxiv-cs-lg

PolyUQuest: Verifiable Structure-Aware Web RAG over Heterogeneous Graphs

arXiv:2607.08269v1 Announce Type: new Abstract: Existing retrieval-augmented generation (RAG) systems treat web pages as flat text, losing the structural and semantic signals encoded in HTML. We prese

Pose-to-Biomechanics: Bridging 3D Human Pose Estimation and Biomechanical Attribute Prediction

arXiv:2607.08725v1 Announce Type: cross Abstract: Recent progress in 3D human pose estimation has made markerless recovery of skeletal motion increasingly accurate and scalable. However, most pose est

PRGCN: A Graph Memory Network for Cross-Sequence Pattern Reuse in 3D Human Pose Estimation

arXiv:2510.19475v2 Announce Type: replace Abstract: Monocular 3D human pose estimation remains a fundamentally ill-posed inverse problem due to the inherent depth ambiguity in 2D-to-3D lifting. While

researcharxiv-cs-cv

Psychological Competence as a Missing Dimension in AI Evaluation

arXiv:2607.08285v1 Announce Type: new Abstract: Current AI evaluation frameworks focus primarily on technical performance, including accuracy, robustness, reasoning ability, and policy compliance. The

Reinforcing the Generation Order of Multimodal Masked Diffusion Models

arXiv:2607.08056v1 Announce Type: cross Abstract: Diffusion Language Models (DLMs) have recently achieved substantial progress in natural language generation tasks. Recent research demonstrates that a

RetailBench: Evaluating Long-Horizon Autonomous Decision-Making and Strategy Stability of LLM Agents in Realistic Retail Environments

arXiv:2603.16453v3 Announce Type: replace Abstract: Large language model (LLM) agents have made rapid progress on short-horizon, well-scoped tasks, yet their ability to sustain coherent decisions in d

Rethinking LLM-as-a-Judge: Representation-as-a-Judge with Small Language Models via Semantic Capacity Asymmetry

arXiv:2601.22588v2 Announce Type: replace-cross Abstract: Large language models (LLMs) are widely used as reference-free evaluators via prompting, but this 'LLM-as-a-Judge' paradigm is costly, opaque,

Local Ai

RhyMix: A Lightweight Adaptive Multi-Rhythm Network for Long-Term Time Series Forecasting

arXiv:2607.08234v1 Announce Type: cross Abstract: Real-world time series exhibit complex dynamics characterized by multiple simultaneous temporal patterns: short-term fluctuations, periodic seasonal c

local-aiarxiv-cs-ai

Scalable and Culturally Specific Stereotype Dataset Construction via Human-LLM Collaboration

arXiv:2607.07895v1 Announce Type: new Abstract: Research on stereotypes in large language models (LLMs) has largely focused on English-speaking contexts, due to the lack of datasets in other languages

Applications

SkelGen4D: Weakly-Supervised Skeleton-Based 4D Generation for Text-Driven Mesh Animation

arXiv:2607.08246v1 Announce Type: new Abstract: We study 4D generation to synthesize temporally coherent sequences of 3D geometry for animation and content creation. In contrast to existing SDS-based

applicationsarxiv-cs-cv

SkillPlug: Unsupervised Skill Mining for Few-Shot Adaptation in Robotic Manipulation

arXiv:2607.08354v1 Announce Type: new Abstract: Learning transferable visuomotor imitation policies that generalize across diverse manipulation tasks and adapt rapidly to new tasks from only a handful

safetyarxiv-cs-ro