Search: “model-releases”

Green Shielding: A User-Centric Approach Towards Trustworthy AI

arXiv:2604.24700v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly deployed, yet their outputs can be highly sensitive to routine, non-adversarial variation in how users p

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Model Releases

Group Orthogonal Low-Rank Adaptation for RGB-T Tracking

DGX agent

arXiv:2512.05359v2 Announce Type: replace Abstract: Parameter-efficient fine-tuning has emerged as a promising paradigm in RGB-T tracking, enabling downstream task adaptation by freezing pretrained pa

model-releasesarxiv-cs-cv

28 Apr 2026

GSAR: Typed Grounding for Hallucination Detection and Recovery in Multi-Agent LLMs

arXiv:2604.23366v1 Announce Type: new Abstract: Autonomous multi-agent LLM systems are increasingly deployed to investigate operational incidents and produce structured diagnostic reports. Their trust

GSC-QEMit: A Telemetry-Driven Hierarchical Forecast-and-Bandit Framework for Adaptive Quantum Error Mitigation

arXiv:2604.24551v1 Announce Type: cross Abstract: Quantum error mitigation (QEM) is essential for extracting reliable results from near-term quantum devices, yet practical deployments must balance mit

HAC: Parameter-Efficient Hyperbolic Adaptation of CLIP for Zero-Shot VQA

arXiv:2604.23665v1 Announce Type: new Abstract: Recent advances in representation learning have shown that hyperbolic geometry can offer a more expressive alternative to the Euclidean embeddings used

HalalBench: A Multilingual OCR Benchmark for Food Packaging Ingredient Extraction

arXiv:2604.22754v1 Announce Type: cross Abstract: No standardized benchmark exists for evaluating OCR on food packaging, despite its critical role in automated halal food verification. Existing benchm

Hamiltonian Graph Inference Networks: Joint structure discovery and dynamics prediction for lattice Hamiltonian systems from trajectory data

arXiv:2604.23606v1 Announce Type: new Abstract: Lattice Hamiltonian systems underpin models across condensed matter, nonlinear optics, and biophysics, yet learning their dynamics from data is obstruct

HBGSA: Hydrogen Bond Graph with Self-Attention for Drug-Target Binding Affinity Prediction

arXiv:2604.23115v1 Announce Type: new Abstract: Accurate prediction of drug-target binding affinity accelerates drug discovery by prioritizing compounds for experimental validation. Current methods fa

Hierarchical Spatio-Channel Clustering for Efficient Model Compression in Medical Image Analysis

arXiv:2604.23375v1 Announce Type: new Abstract: Convolutional neural networks (CNNs) have become increasingly difficult to deploy in resource-constrained environments due to their large memory and com

High-Dimensional Private Linear Regression with Optimal Rates

arXiv:2505.16329v2 Announce Type: replace-cross Abstract: Differentially private (DP) linear regression has received significant attention in the recent theoretical literature, with several approaches

How Sensitive Are Safety Benchmarks to Judge Configuration Choices?

arXiv:2604.24074v1 Announce Type: new Abstract: Safety benchmarks such as HarmBench rely on LLM judges to classify model responses as harmful or safe, yet the judge configuration, namely the combinati

Hybrid JIT-CUDA Graph Optimization for Low-Latency Large Language Model Inference

arXiv:2604.23467v1 Announce Type: cross Abstract: Large Language Models (LLMs) have achieved strong performance across natural language and multimodal tasks, yet their practical deployment remains con

ImmerIris: A Large-Scale Dataset and Benchmark for Off-Axis and Unconstrained Iris Recognition in Immersive Applications

arXiv:2510.10113v3 Announce Type: replace Abstract: Recently, iris recognition is regaining prominence in immersive applications such as extended reality as a means of seamless user identification. Th

IMPA-Net: Meteorology-Aware Multi-Scale Attention and Dynamic Loss for Extreme Convective Radar Nowcasting

arXiv:2604.24224v1 Announce Type: new Abstract: Short-range prediction of convective precipitation from weather radar observations is essential for severe weather warnings. However, deep learning mode

Improving Vision-language Models with Perception-centric Process Reward Models

arXiv:2604.24583v1 Announce Type: new Abstract: Recent advancements in reinforcement learning with verifiable rewards (RLVR) have significantly improved the complex reasoning ability of vision-languag

INHerit-SG: Incremental Hierarchical Semantic Scene Graphs with RAG-Style Retrieval

model-releasesarxiv-cs-ro

arXiv:2602.12971v2 Announce Type: replace Abstract: Driven by recent advancements in foundation models, semantic scene graphs have emerged as a promising paradigm for high-level 3D environmental abstr

InquireMobile: Teaching VLM-based Mobile Agent to Request Human Assistance via Reinforcement Fine-Tuning

arXiv:2508.19679v2 Announce Type: replace Abstract: Recent advances in Vision-Language Models (VLMs) have enabled mobile agents to perceive and interact with real-world mobile environments based on hu

Insert In Style: A Zero-Shot Generative Framework for Harmonious Cross-Domain Object Composition

arXiv:2511.15197v2 Announce Type: replace Abstract: Reference-based object composition involves integrating foreground reference image with background scene to produce harmonious fused image. This tas

IntrAgent: An LLM Agent for Content-Grounded Information Retrieval through Literature Review

arXiv:2604.22861v1 Announce Type: cross Abstract: Scientific research relies on accurate information retrieval from literature to support analytical decisions. In this work, we introduce a new task, I

Jailbreaking Frontier Foundation Models Through Intention Deception

arXiv:2604.24082v1 Announce Type: cross Abstract: Large (vision-)language models exhibit remarkable capability but remain highly susceptible to jailbreaking. Existing safety training approaches aim to

JudgeSense: A Benchmark for Prompt Sensitivity in LLM-as-a-Judge Systems

arXiv:2604.23478v1 Announce Type: new Abstract: Large language models are increasingly deployed as automated judges for evaluating other models, yet the stability of their verdicts under semantically

Judging the Judges: A Systematic Evaluation of Bias Mitigation Strategies in LLM-as-a-Judge Pipelines

arXiv:2604.23178v1 Announce Type: new Abstract: LLM-as-a-Judge has become the dominant paradigm for evaluating language model outputs, yet LLM judges exhibit systematic biases that compromise evaluati

K-MetBench: A Multi-Dimensional Benchmark for Fine-Grained Evaluation of Expert Reasoning, Locality, and Multimodality in Meteorology

arXiv:2604.24645v1 Announce Type: cross Abstract: The development of practical (multimodal) large language model assistants for Korean weather forecasters is hindered by the absence of a multidimensio

KLong: Training LLM Agent for Extremely Long-horizon Tasks

arXiv:2602.17547v3 Announce Type: replace Abstract: This paper introduces KLong, an open-source LLM agent trained to solve extremely long-horizon tasks. The principle is to first cold-start the model

Large Language Models as Virtual Survey Respondents: Evaluating Sociodemographic Response Generation

arXiv:2509.06337v2 Announce Type: replace Abstract: Questionnaire-based surveys are foundational to social science research and public policymaking, yet traditional survey methods remain costly, time-

Latency and Cost of Multi-Agent Intelligent Tutoring at Scale

arXiv:2604.24110v1 Announce Type: cross Abstract: Multi-agent LLM tutoring systems improve response quality through agent specialization, but each student query triggers several concurrent API calls w

Layerwise Convergence Fingerprints for Runtime Misbehavior Detection in Large Language Models

arXiv:2604.24542v1 Announce Type: cross Abstract: Large language models deployed at runtime can misbehave in ways that clean-data validation cannot anticipate: training-time backdoors lie dormant unti

LearnAlign: Data Selection for LLM Reinforcement Learning with Improved Gradient Alignment

arXiv:2506.11480v4 Announce Type: replace-cross Abstract: Reinforcement learning with verifiable rewards (RLVR) has become a key technique for enhancing LLMs' reasoning abilities, yet its data ineffic

Learning Gradient-based Mixup with Extrapolation toward Flatter Minima for Domain Generalization

arXiv:2209.14742v2 Announce Type: replace Abstract: To address distribution shifts between training and test data, domain generalization (DG) leverages multiple source domains to learn a model that ge

Learning in Blocks: A Multi Agent Debate Assisted Personalized Adaptive Learning Framework for Language Learning

arXiv:2604.22770v1 Announce Type: cross Abstract: Most digital language learning curricula rely on discrete-item quizzes that test recall rather than applied conversational proficiency. When progressi

Learning Latent Graph Geometry via Fixed-Point Schrodinger-Type Activation: A Theoretical Study

arXiv:2507.20088v3 Announce Type: replace Abstract: We study neural architectures in which each hidden layer is defined by the stationary state of a dissipative Schrodinger-type dynamics on a learned

Learning to Conceal Risk: Controllable Multi-turn Red Teaming for LLMs in the Financial Domain

arXiv:2509.10546v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) are increasingly deployed in finance, where unsafe behavior can lead to serious regulatory risks. However, most r

Learning Under Low Illumination: A Dataset and Algorithm for Traffic Sign Recognition

arXiv:2511.17183v2 Announce Type: replace Abstract: Traffic signboards are vital for road safety and intelligent transportation systems, enabling navigation and autonomous driving. Yet, recognizing tr

LEGO: An LLM Skill-Based Front-End Design Generation Platform

arXiv:2604.23355v1 Announce Type: new Abstract: Existing LLM-based EDA agents are often isolated task-specific systems. This leads to repeated engineering effort and limited reuse of successful design

Less Is More: Engineering Challenges of On-Device Small Language Model Integration in a Mobile Application

arXiv:2604.24636v1 Announce Type: cross Abstract: On-device Small Language Models (SLMs) promise fully offline, private AI experiences for mobile users (no cloud dependency, no data leaving the device

Leveraging LLMs for Multi-File DSL Code Generation: An Industrial Case Study

arXiv:2604.24678v1 Announce Type: cross Abstract: Large language models (LLMs) perform strongly on general-purpose code generation, yet their applicability to enterprise domain-specific languages (DSL

Lightweight and Production-Ready PDF Visual Element Parsing

arXiv:2604.23276v1 Announce Type: cross Abstract: PDF documents contain critical visual elements such as figures, tables, and forms whose accurate extraction is essential for document understanding an

Linear-Nonlinear Fusion Neural Operator for Partial Differential Equations

arXiv:2603.24143v2 Announce Type: replace Abstract: Neural operator learning directly constructs the mapping relationship from the equation parameter space to the solution space, enabling efficient di

LLM-Assisted Op-Amp Behavioral-Level Design via Agentic Human-Mimicking Reasoning

arXiv:2601.21321v2 Announce Type: replace Abstract: This paper proposes White-Op, an operational amplifier (op-amp) behavioral-level parameter design framework assisted by the human-mimicking reasonin

LLM-Guided Agentic Floor Plan Parsing for Accessible Indoor Navigation of Blind and Low-Vision People

arXiv:2604.23970v1 Announce Type: new Abstract: Indoor navigation remains a critical accessibility challenge for the blind and low-vision (BLV) individuals, as existing solutions rely on costly per-bu

LLM4SCREENLIT: Recommendations on Assessing the Performance of Large Language Models for Screening Literature in Systematic Reviews

arXiv:2511.12635v2 Announce Type: replace-cross Abstract: Context: Large language models (LLMs) are increasingly used to screen literature for systematic reviews (SRs), but the standard confusion-matr

Long-Context Aware Upcycling: A New Frontier for Hybrid LLM Scaling

arXiv:2604.24715v1 Announce Type: new Abstract: Hybrid sequence models that combine efficient Transformer components with linear sequence modeling blocks are a promising alternative to pure Transforme

LongFlow: Efficient KV Cache Compression for Reasoning Models

arXiv:2603.11504v2 Announce Type: replace-cross Abstract: Recent reasoning models such as OpenAI-o1 and DeepSeek-R1 have shown strong performance on complex tasks including mathematical reasoning and

Looking for the Bottleneck in Fine-grained Temporal Relation Classification

arXiv:2604.24620v1 Announce Type: new Abstract: Temporal relation classification is the task of determining the temporal relation between pairs of temporal entities in a text. Despite recent advanceme

Lost in Decoding? Reproducing and Stress-Testing the Look-Ahead Prior in Generative Retrieval

arXiv:2604.23396v1 Announce Type: cross Abstract: Generative retrieval (GR) ranks documents by autoregressively generating document identifiers. Because many GR methods rely on trie-constrained beam s

Lost in the Vibrations: Vision Language Models Fail the Dynamic Gauges Test

arXiv:2604.22829v1 Announce Type: new Abstract: The digital transformation of industrial manufacturing increasingly relies on the ability of autonomous robots to interact with legacy infrastructure, p

Machine Learning and Deep Learning Models for Short Term Electricity Price Forecasting in Australia's National Electricity Market

arXiv:2604.23908v1 Announce Type: new Abstract: Short term electricity price forecast is essential in competitive power markets, yet electricity price series exhibit high volatility, irregularity, and

Majorization-Guided Test-Time Adaptation for Vision-Language Models under Modality-Specific Shift

arXiv:2604.24602v1 Announce Type: new Abstract: Vision-language models transfer well in zero-shot settings, but at deployment the visual and textual branches often shift asymmetrically. Under this con