Search: “models”

FedRio: Personalized Federated Social Bot Detection via Cooperative Reinforced Contrastive Adversarial Distillation

arXiv:2604.10678v1 Announce Type: new Abstract: Social bot detection is critical to the stability and security of online social platforms. However, current state-of-the-art bot detection models are la

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Model Releases

From GPT-3 to GPT-5: Mapping their capabilities, scope, limitations, and consequences

DGX agent

arXiv:2604.10332v1 Announce Type: new Abstract: We present the progress of the GPT family from GPT-3 through GPT-3.5, GPT-4, GPT-4 Turbo, GPT-4o, GPT-4.1, and the GPT-5 family. Our work is comparative

model-releasesarxiv-cs-ai

14 Apr 2026

Frugal Knowledge Graph Construction with Local LLMs: A Zero-Shot Pipeline, Self-Consistency and Wisdom of Artificial Crowds

arXiv:2604.11104v1 Announce Type: new Abstract: This paper presents an empirical study of a multi-model zero-shot pipeline for knowledge graph construction and exploitation, executed entirely through

GLEaN: A Text-to-image Bias Detection Approach for Public Comprehension

arXiv:2604.09923v1 Announce Type: new Abstract: Text-to-image (T2I) models, and their encoded biases, increasingly shape the visual media the public encounters. While researchers have produced a rich

safetyarxiv-cs-ai

Learning Robustness at Test-Time from a Non-Robust Teacher

arXiv:2604.11590v1 Announce Type: new Abstract: Nowadays, pretrained models are increasingly used as general-purpose backbones and adapted at test-time to downstream environments where target data are

LIFT: A Novel Framework for Enhancing Long-Context Understanding of LLMs via Long Input Fine-Tuning

arXiv:2502.14644v5 Announce Type: replace Abstract: Long context understanding remains challenging for large language models due to their limited context windows. This paper introduces Long Input Fine

Measuring and curing reasoning rigidity: from decorative chain-of-thought to genuine faithfulness

arXiv:2603.22816v3 Announce Type: replace-cross Abstract: Language models increasingly show their work by writing step-by-step reasoning before answering. But are these steps genuinely used, or is the

Mirai: Autoregressive Visual Generation Needs Foresight

arXiv:2601.14671v2 Announce Type: replace Abstract: Autoregressive (AR) visual generators model images as sequences of discrete tokens and are trained with a next-token likelihood objective. This stri

MoEITS: A Green AI approach for simplifying MoE-LLMs

arXiv:2604.10603v1 Announce Type: cross Abstract: Large language models are transforming all areas of academia and industry, attracting the attention of researchers, professionals, and the general pub

MosaicMRI: A Diverse Dataset and Benchmark for Raw Musculoskeletal MRI

arXiv:2604.11762v1 Announce Type: new Abstract: Deep learning underpins a wide range of applications in MRI, including reconstruction, artifact removal, and segmentation. However, progress has been dr

OmniScript: Towards Audio-Visual Script Generation for Long-Form Cinematic Video

arXiv:2604.11102v1 Announce Type: new Abstract: Current multimodal large language models (MLLMs) have demonstrated remarkable capabilities in short-form video understanding, yet translating long-form

Parameter Efficient Fine-tuning for Domain-specific Gastrointestinal Disease Recognition

arXiv:2604.10451v1 Announce Type: new Abstract: Despite recent advancements in the field of medical image analysis with the use of pretrained foundation models, the issue of distribution shifts betwee

Prompt Relay: Inference-Time Temporal Control for Multi-Event Video Generation

arXiv:2604.10030v1 Announce Type: new Abstract: Video diffusion models have achieved remarkable progress in generating high-quality videos. However, these models struggle to represent the temporal suc

safetyarxiv-cs-cv

Local Ai

ProPhy: Progressive Physical Alignment for Dynamic World Simulation

arXiv:2512.05564v2 Announce Type: replace Abstract: Recent advances in video generation have shown remarkable potential for constructing world simulators. However, current models still struggle to pro

local-aiarxiv-cs-cv

Applications

Quantization Robustness to Input Degradations for Object Detection

arXiv:2508.19600v2 Announce Type: replace Abstract: Post-training quantization (PTQ) is crucial for deploying efficient object detection models, like YOLO, on resource-constrained devices. However, th

applicationsarxiv-cs-cv

Radiology Report Generation for Low-Quality X-Ray Images

arXiv:2604.10188v1 Announce Type: new Abstract: Vision-Language Models (VLMs) have significantly advanced automated Radiology Report Generation (RRG). However, existing methods implicitly assume high-

Hardware

Relational Probing: LM-to-Graph Adaptation for Financial Prediction

arXiv:2604.10212v1 Announce Type: new Abstract: Language models can be used to identify relationships between financial entities in text. However, while structured output mechanisms exist, prompting-b

hardwarearxiv-cs-cl

Signal-Aware Conditional Diffusion Surrogates for Transonic Wing Pressure Prediction

arXiv:2604.11263v1 Announce Type: cross Abstract: Accurate and efficient surrogate models for aerodynamic surface pressure fields are essential for accelerating aircraft design and analysis, yet deter

researcharxiv-cs-lg

SMART: When is it Actually Worth Expanding a Speculative Tree?

arXiv:2604.09731v1 Announce Type: cross Abstract: Tree-based speculative decoding accelerates autoregressive generation by verifying a branching tree of draft tokens in a single target-model forward p

STARS: Skill-Triggered Audit for Request-Conditioned Invocation Safety in Agent Systems

arXiv:2604.10286v1 Announce Type: new Abstract: Autonomous language-model agents increasingly rely on installable skills and tools to complete user tasks. Static skill auditing can expose capability s

Training-Free Cross-Lingual Dysarthria Severity Assessment via Phonological Subspace Analysis in Self-Supervised Speech Representations

arXiv:2604.10123v1 Announce Type: new Abstract: Dysarthric speech severity assessment typically requires trained clinicians or supervised models built from labelled pathological speech, limiting scala

safetyarxiv-cs-cl

Tutorials

Transformers for dynamical systems learn transfer operators in-context

arXiv:2602.18679v2 Announce Type: replace Abstract: Large-scale foundation models for scientific machine learning adapt to physical settings unseen during training, such as zero-shot transfer between

tutorialsarxiv-cs-lg

VS-Bench: Evaluating VLMs for Strategic Abilities in Multi-Agent Environments

arXiv:2506.02387v3 Announce Type: replace Abstract: Recent advancements in Vision Language Models (VLMs) have expanded their capabilities to interactive agent tasks, yet existing benchmarks remain lim

When Meaning Isn't Literal: Exploring Idiomatic Meaning Across Languages and Modalities

arXiv:2604.10787v1 Announce Type: new Abstract: Idiomatic reasoning, deeply intertwined with metaphor and culture, remains a blind spot for contemporary language models, whose progress skews toward su

When Verification Fails: How Compositionally Infeasible Claims Escape Rejection

arXiv:2604.10990v1 Announce Type: cross Abstract: Scientific claim verification, the task of determining whether claims are entailed by scientific evidence, is fundamental to establishing discoveries

researcharxiv-cs-ai

Accurate and Reliable Uncertainty Estimates for Deterministic Predictions Extensions to Under and Overpredictions

model-releasesarxiv-cs-lg

arXiv:2604.08755v1 Announce Type: cross Abstract: Computational models support high-stakes decisions across engineering and science, and practitioners increasingly seek probabilistic predictions to qu

AsymLoc: Towards Asymmetric Feature Matching for Efficient Visual Localization

arXiv:2604.09445v1 Announce Type: new Abstract: Precise and real-time visual localization is critical for applications like AR/VR and robotics, especially on resource-constrained edge devices such as

Applications

Confident in a Confidence Score: Investigating the Sensitivity of Confidence Scores to Supervised Fine-Tuning

arXiv:2604.08974v1 Announce Type: new Abstract: Uncertainty quantification is a set of techniques that measure confidence in language models. They can be used, for example, to detect hallucinations or

applicationsarxiv-cs-cl

EfficientSign: An Attention-Enhanced Lightweight Architecture for Indian Sign Language Recognition

arXiv:2604.08694v1 Announce Type: new Abstract: How do you build a sign language recognizer that works on a phone? That question drove this work. We built EfficientSign, a lightweight model which take

researcharxiv-cs-cv

Enhancing LLM Problem Solving via Tutor-Student Multi-Agent Interaction

arXiv:2604.08931v1 Announce Type: new Abstract: Human cognitive development is shaped not only by individual effort but by structured social interaction, where role-based exchanges such as those betwe

Evolutionary Optimization Trumps Adam Optimization on Embedding Space Exploration

arXiv:2511.03913v2 Announce Type: replace-cross Abstract: Deep diffusion models have revolutionized image generation by producing high-quality outputs. However, achieving specific objectives with thes

safetyarxiv-cs-ai

GeoMMBench and GeoMMAgent: Toward Expert-Level Multimodal Intelligence in Geoscience and Remote Sensing

arXiv:2604.08896v1 Announce Type: new Abstract: Recent advances in multimodal large language models (MLLMs) have accelerated progress in domain-oriented AI, yet their development in geoscience and rem

Hierarchical Alignment: Enforcing Hierarchical Instruction-Following in LLMs through Logical Consistency

arXiv:2604.09075v1 Announce Type: new Abstract: Large language models increasingly operate under multiple instructions from heterogeneous sources with different authority levels, including system poli

safetyarxiv-cs-cl

Many-Tier Instruction Hierarchy in LLM Agents

arXiv:2604.09443v1 Announce Type: cross Abstract: Large language model agents receive instructions from many sources-system messages, user prompts, tool outputs, and more-each carrying different level

Many Ways to Be Fake: Benchmarking Fake News Detection Under Strategy-Driven AI Generation

arXiv:2604.09514v1 Announce Type: new Abstract: Recent advances in large language models (LLMs) have enabled the large-scale generation of highly fluent and deceptive news-like content. While prior wo

Mitigating Extrinsic Gender Bias for Bangla Classification Tasks

arXiv:2411.10636v2 Announce Type: replace-cross Abstract: In this study, we investigate extrinsic gender bias in Bangla pretrained language models, a largely underexplored area in low-resource languag

MixFlow: Mixed Source Distributions Improve Rectified Flows

arXiv:2604.09181v1 Announce Type: new Abstract: Diffusion models and their variations, such as rectified flows, generate diverse and high-quality images, but they are still hindered by slow iterative

safetyarxiv-cs-cv

Mnemis: Dual-Route Retrieval on Hierarchical Graphs for Long-Term LLM Memory

arXiv:2602.15313v2 Announce Type: replace Abstract: AI Memory, specifically how models organizes and retrieves historical messages, becomes increasingly valuable to Large Language Models (LLMs), yet e

NCL-BU at SemEval-2026 Task 3: Fine-tuning XLM-RoBERTa for Multilingual Dimensional Sentiment Regression

arXiv:2604.08923v1 Announce Type: new Abstract: Dimensional Aspect-Based Sentiment Analysis (DimABSA) extends traditional ABSA from categorical polarity labels to continuous valence-arousal (VA) regre

Noise-Aware In-Context Learning for Hallucination Mitigation in ALLMs

arXiv:2604.09021v1 Announce Type: cross Abstract: Auditory large language models (ALLMs) have demonstrated strong general capabilities in audio understanding and reasoning tasks. However, their reliab

Overstating Attitudes, Ignoring Networks: LLM Biases in Simulating Misinformation Susceptibility

arXiv:2602.04674v2 Announce Type: replace-cross Abstract: Large language models (LLMs) are increasingly used as proxies for human judgment in computational social science, yet their ability to reprodu

researcharxiv-cs-ai

PRADA: Probability-Ratio-Based Attribution and Detection of Autoregressive-Generated Images

arXiv:2511.20068v2 Announce Type: replace Abstract: Autoregressive (AR) image generation has recently emerged as a powerful paradigm for image synthesis. Leveraging the generation principle of large l

researcharxiv-cs-cv

Reasoning in a Combinatorial and Constrained World: Benchmarking LLMs on Natural-Language Combinatorial Optimization

arXiv:2602.02188v2 Announce Type: replace Abstract: While large language models (LLMs) have shown strong performance in math and logic reasoning, their ability to handle combinatorial optimization (CO

SAGE: A Service Agent Graph-guided Evaluation Benchmark

arXiv:2604.09285v1 Announce Type: new Abstract: The development of Large Language Models (LLMs) has catalyzed automation in customer service, yet benchmarking their performance remains challenging. Ex

Skill-Conditioned Visual Geolocation for Vision-Language

arXiv:2604.09025v1 Announce Type: cross Abstract: Vision-language models (VLMs) have shown a promising ability in image geolocation, but they still lack structured geographic reasoning and the capacit

SUPERNOVA: Eliciting General Reasoning in LLMs with Reinforcement Learning on Natural Instructions

arXiv:2604.08477v1 Announce Type: cross Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) has significantly improved large language model (LLM) reasoning in formal domains such as mathem

researcharxiv-cs-cl

UIPress: Bringing Optical Token Compression to UI-to-Code Generation

arXiv:2604.09442v1 Announce Type: new Abstract: UI-to-Code generation requires vision-language models (VLMs) to produce thousands of tokens of structured HTML/CSS from a single screenshot, making visu

researcharxiv-cs-cl

Tutorials

You Can't Fight in Here! This is BBS!

arXiv:2604.09501v1 Announce Type: new Abstract: Norm, the formal theoretical linguist, and Claudette, the computational language scientist, have a lovely time discussing whether modern language models

tutorialsarxiv-cs-cl