Search: “benchmark”

How Well Does GPT-4o Understand Vision? Evaluating Multimodal Foundation Models on Standard Computer Vision Tasks

arXiv:2507.01955v3 Announce Type: replace Abstract: Multimodal foundation models (MFMs), such as GPT-4o, have recently made remarkable progress. However, their detailed visual understanding beyond que

Human

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Model Releases

Jailbroken Frontier Models Retain Their Capabilities

DGX agent

arXiv:2605.00267v1 Announce Type: new Abstract: As language model safeguards become more robust, attackers are pushed toward developing increasingly complex jailbreaks. Prior work has found that this

model-releasesarxiv-cs-lg

4 May 2026

Learning from the Unseen: Generative Data Augmentation for Geometric-Semantic Accident Anticipation

arXiv:2605.00051v1 Announce Type: new Abstract: Anticipating traffic accidents is a critical yet unresolved problem for autonomous driving, hindered by the inherent complexity of modeling interactions

OTSS: Output-Targeted Soft Segmentation for Contextual Decision-Weight Learning

arXiv:2605.00193v1 Announce Type: new Abstract: Many machine learning systems make constrained decisions by optimizing factorized objectives, but the context-specific objective is often treated as fix

Unlocking Zero-Shot Geospatial Reasoning via Indirect Rewards

arXiv:2510.00072v2 Announce Type: replace Abstract: Training robust reasoning vision-language models (VLMs) in rare domains (such as geospatial) is fundamentally constrained by supervision scarcity. W

safetyarxiv-cs-cv

ViLegalNLI: Natural Language Inference for Vietnamese Legal Texts

arXiv:2605.00116v1 Announce Type: new Abstract: In this article, we introduce ViLegalNLI, the first large-scale Vietnamese Natural Language Inference (NLI) dataset specifically constructed for the leg

World Model for Robot Learning: A Comprehensive Survey

arXiv:2605.00080v1 Announce Type: cross Abstract: World models, which are predictive representations of how environments evolve under actions, have become a central component of robot learning. They s

safetyarxiv-cs-cv

AesRM: Improving Video Aesthetics with Expert-Level Feedback

arXiv:2604.28078v1 Announce Type: new Abstract: Despite rapid advances in photorealistic video generation, real-world applications such as filmmaking require video aesthetics, e.g., harmonious colors

CareGuardAI: Context-Aware Multi-Agent Guardrails for Clinical Safety & Hallucination Mitigation in Patient-Facing LLMs

arXiv:2604.26959v1 Announce Type: cross Abstract: Integrating large language models (LLMs) into patient-facing healthcare systems offers significant potential to improve access to medical information.

CL-bench Life: Can Language Models Learn from Real-Life Context?

arXiv:2604.27043v1 Announce Type: new Abstract: Today's AI assistants such as OpenClaw are designed to handle context effectively, making context learning an increasingly important capability for mode

Cross-Lingual Sentiment Misalignment: Auditing Multilingual Language Models for Inversion Risk, Dialectal Representation, and Affective Stability

arXiv:2602.17469v2 Announce Type: replace Abstract: Recent advances in multilingual representation learning aim to bridge the performance gap between high- and low-resource languages, yet their abilit

safetyarxiv-cs-cl

DeepTutor: Towards Agentic Personalized Tutoring

arXiv:2604.26962v1 Announce Type: cross Abstract: Education represents one of the most promising real-world applications for Large Language Models (LLMs). However, conventional tutoring systems rely o

Do What I Say: A Spoken Prompt Dataset for Instruction-Following

arXiv:2603.09881v2 Announce Type: replace Abstract: Speech Large Language Models (SLLMs) have rapidly expanded, supporting a wide range of tasks. These models are typically evaluated using text prompt

HealthBench Professional: Evaluating Large Language Models on Real Clinician Chats

arXiv:2604.27470v1 Announce Type: new Abstract: Millions of clinicians use ChatGPT to support clinical care, but evaluations of the most common use cases in model-clinician conversations are limited.

InteractWeb-Bench: Can Multimodal Agent Escape Blind Execution in Interactive Website Generation?

arXiv:2604.27419v1 Announce Type: new Abstract: With the advancement of multimodal large language models (MLLMs) and coding agents, the website development has shifted from manual programming to agent

LA-Pose: Latent Action Pretraining Meets Pose Estimation

arXiv:2604.27448v1 Announce Type: new Abstract: This paper revisits camera pose estimation through the lens of self-supervised pretraining, focusing on inverse-dynamics pretraining as a scalable alter

safetyarxiv-cs-cv

Latent-GRPO: Group Relative Policy Optimization for Latent Reasoning

arXiv:2604.27998v1 Announce Type: cross Abstract: Latent reasoning offers a more efficient alternative to explicit reasoning by compressing intermediate reasoning into continuous representations and s

safetyarxiv-cs-cl

MAEO: Multiobjective Animorphic Ensemble Optimization for Scalable Large-scale Engineering Applications

arXiv:2604.26973v1 Announce Type: cross Abstract: Multiobjective optimization remains challenging for many scientific and engineering problems due to the need to balance convergence, diversity, and co

MCPHunt: An Evaluation Framework for Cross-Boundary Data Propagation in Multi-Server MCP Agents

arXiv:2604.27819v1 Announce Type: new Abstract: Multi-server MCP agents create an information-flow control problem: faithful tool composition can turn individually benign read/write permissions into c

People-Centred Medical Image Analysis

arXiv:2604.26991v1 Announce Type: cross Abstract: Recent advances in data-centric medical AI have produced highly accurate diagnostic systems, but the emphasis on data curation and performance metrics

PVeRA: Probabilistic Vector-Based Random Matrix Adaptation

arXiv:2512.07703v2 Announce Type: replace Abstract: Large foundation models have emerged in the last years and are pushing performance boundaries for a variety of tasks. Training or even finetuning su

Step-level Optimization for Efficient Computer-use Agents

arXiv:2604.27151v1 Announce Type: new Abstract: Computer-use agents provide a promising path toward general software automation because they can interact directly with arbitrary graphical user interfa

TripVVT: A Large-Scale Triplet Dataset and a Coarse-Mask Baseline for In-the-Wild Video Virtual Try-On

arXiv:2604.27958v1 Announce Type: new Abstract: Due to the scarcity of large-scale in-the-wild triplet data and the improper use of masks, the performance of video virtual try-on models remains limite

A self-evolving agent for explainable diagnosis of DFT-experiment band-gap mismatch

arXiv:2604.26703v1 Announce Type: cross Abstract: Standard density functional theory (DFT) routinely misclassifies the electronic ground state of correlated and structurally complex compounds, predict

AdaMem: Adaptive User-Centric Memory for Long-Horizon Dialogue Agents

arXiv:2603.16496v2 Announce Type: replace Abstract: Large language model (LLM) agents increasingly rely on external memory to support long-horizon interaction, personalized assistance, and multi-step

COP-GEN: Latent Diffusion Transformer for Copernicus Earth Observation Data

arXiv:2603.03239v2 Announce Type: replace Abstract: Earth observation applications increasingly rely on data from multiple sensors, including optical, radar, elevation, and land-cover. Relationships b

CurEvo: Curriculum-Guided Self-Evolution for Video Understanding

arXiv:2604.26707v1 Announce Type: new Abstract: Recent advances in self-evolution video understanding frameworks have demonstrated the potential of autonomous learning without human annotations. Howev

Decoupled Prototype Matching with Vision Foundation Models for Few-Shot Industrial Object Detection

arXiv:2604.26404v1 Announce Type: new Abstract: Industrial object detection systems typically rely on large annotated datasets, which are expensive to collect and challenging to maintain in industrial

DORA: A Scalable Asynchronous Reinforcement Learning System for Language Model Training

arXiv:2604.26256v1 Announce Type: new Abstract: Reinforcement learning (RL) has become a critical paradigm for LLM post-training, yet the rollout phase -- accounting for 50--80% of total step time --

safetyarxiv-cs-lg

Electricity price forecasting across Norway's five bidding zones in the post-crisis era

arXiv:2604.26634v1 Announce Type: new Abstract: Norway's electricity market is heavily dominated by hydropower, but the 2021--2022 energy crisis and stronger integration with Continental Europe have f

FunFace: Feature Utility and Norm Estimation for Face Recognition

arXiv:2604.26598v1 Announce Type: new Abstract: Face Recognition (FR) is used in a variety of application domains, from entertainment and banking to security and surveillance. Such applications rely o

researcharxiv-cs-cv

HumanOmni-Speaker: Identifying Who said What and When

arXiv:2603.21664v2 Announce Type: replace Abstract: While Omni-modal Large Language Models have made strides in joint sensory processing, they fundamentally struggle with a cornerstone of human intera

Inferix: A Block-Diffusion based Next-Generation Inference Engine for World Simulation

arXiv:2511.20714v2 Announce Type: replace-cross Abstract: World models serve as core simulators for fields such as agentic AI, embodied AI, and gaming, capable of generating long, physically realistic

Learning to Route Electric Trucks Under Operational Uncertainty

arXiv:2604.26566v1 Announce Type: cross Abstract: Electric truck operations require routing decisions that remain feasible under limited battery range, long charging times, travel and energy consumpti

researcharxiv-cs-lg

Multimodal LLMs are not all you need for Pediatric Speech Language Pathology

arXiv:2604.26568v1 Announce Type: new Abstract: Speech Sound Disorders (SSD) affect roughly five percent of children, yet speech-language pathologists face severe staffing shortages and unmanageable c

NeuroPlastic: A Plasticity-Modulated Optimizer for Biologically Inspired Learning Dynamics

arXiv:2604.26297v1 Announce Type: new Abstract: Optimization algorithms are fundamental to modern deep learning, yet most widely used methods rely on update rules based primarily on local gradient sta

Perception Test 2025: Challenge Summary and a Unified VQA Extension

arXiv:2601.06287v2 Announce Type: replace Abstract: The Third Perception Test challenge was organised as a full-day workshop alongside the IEEE/CVF International Conference on Computer Vision (ICCV) 2

ReLoop: Structured Modeling and Behavioral Verification for Reliable LLM-Based Optimization

arXiv:2602.15983v2 Announce Type: replace-cross Abstract: Large language models (LLMs) can translate natural language into optimization code, but silent failures pose a critical risk: code that execut

SciMDR: Advancing Scientific Multimodal Document Reasoning

arXiv:2603.12249v2 Announce Type: replace-cross Abstract: Constructing scientific multimodal document reasoning datasets for foundation model training involves an inherent trade-off among scale, faith

Shorthand for Thought: Compressing LLM Reasoning via Entropy-Guided Supertokens

arXiv:2604.26355v1 Announce Type: new Abstract: Reasoning in Large Language Models incurs significant inference-time compute, yet the token-level information structure of reasoning traces remains unde

StratMem-Bench: Evaluating Strategic Memory Use in Virtual Character Conversation Beyond Factual Recall

arXiv:2604.26243v1 Announce Type: cross Abstract: Achieving realistic human-like conversation for virtual characters requires not only a simple memorization and recall of past events, but also the str

Student Guides Teacher: Weak-to-Strong Inference via Spectral Orthogonal Exploration

arXiv:2601.06160v2 Announce Type: replace Abstract: Large Language Models (LLMs) often suffer from ''Reasoning Collapse'' on challenging mathematical reasoning tasks, where stochastic sampling produce

safetyarxiv-cs-ai

VulStyle: A Multi-Modal Pre-Training for Code Stylometry-Augmented Vulnerability Detection

arXiv:2604.26313v1 Announce Type: cross Abstract: We present VulStyle, a multi-modal software vulnerability detection model that jointly encodes function-level source code, non-terminal Abstract Synta

When to Retrieve During Reasoning: Adaptive Retrieval for Large Reasoning Models

arXiv:2604.26649v1 Announce Type: cross Abstract: Large reasoning models such as DeepSeek-R1 and OpenAI o1 generate extended chains of thought spanning thousands of tokens, yet their integration with

Applications

Why Domain Matters: A Preliminary Study of Domain Effects in Underwater Object Detection

arXiv:2604.26174v1 Announce Type: new Abstract: Domain shift, where deviations between training and deployment data distributions degrade model performance, is a key challenge in underwater environmen

applicationsarxiv-cs-cv

World2VLM: Distilling World Model Imagination into VLMs for Dynamic Spatial Reasoning

arXiv:2604.26934v1 Announce Type: new Abstract: Vision-language models (VLMs) have shown strong performance on static visual understanding, yet they still struggle with dynamic spatial reasoning that

researcharxiv-cs-cv

AdaTooler-V: Adaptive Tool-Use for Images and Videos

arXiv:2512.16918v3 Announce Type: replace Abstract: Recent advances have shown that multimodal large language models (MLLMs) benefit from multimodal interleaved chain-of-thought (CoT) with vision tool

29 Apr 2026

Calibrated Fusion for Heterogeneous Graph-Vector Retrieval in Multi-Hop QA