Search: “model-releases”

IAD-Unify: A Region-Grounded Unified Model for Industrial Anomaly Segmentation, Understanding, and Generation

arXiv:2604.12440v1 Announce Type: cross Abstract: Real-world industrial inspection requires not only localizing defects, but also explaining them in natural language and generating controlled defect e

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Model Releases

IDEA: An Interpretable and Editable Decision-Making Framework for LLMs via Verbal-to-Numeric Calibration

DGX agent

arXiv:2604.12573v1 Announce Type: new Abstract: Large Language Models are increasingly deployed for decision-making, yet their adoption in high-stakes domains remains limited by miscalibrated probabil

model-releasesarxiv-cs-ai

15 Apr 2026

Identifying and Mitigating Gender Cues in Academic Recommendation Letters: An Interpretability Case Study

arXiv:2604.12337v1 Announce Type: new Abstract: Letters of recommendation (LoRs) can carry patterns of implicitly gendered language that can inadvertently influence downstream decisions, e.g. in hirin

Identity as Attractor: Geometric Evidence for Persistent Agent Architecture in LLM Activation Space

arXiv:2604.12016v1 Announce Type: new Abstract: Large language models map semantically related prompts to similar internal representations -- a phenomenon interpretable as attractor-like dynamics. We

Improved particle swarm optimization algorithm: multi-target trajectory optimization for swarm drones

arXiv:2507.13647v2 Announce Type: replace-cross Abstract: Real-time trajectory planning for unmanned aerial vehicles (UAVs) in dynamic environments remains a key challenge due to high computational de

IMSE: Intrinsic Mixture of Spectral Experts Fine-tuning for Test-Time Adaptation

arXiv:2603.07926v3 Announce Type: replace-cross Abstract: Test-time adaptation (TTA) has been widely explored to prevent performance degradation when test data differ from the training distribution. H

INDOTABVQA: A Benchmark for Cross-Lingual Table Understanding in Bahasa Indonesia Documents

arXiv:2604.11970v1 Announce Type: cross Abstract: We introduce INDOTABVQA, a benchmark for evaluating cross-lingual Table Visual Question Answering (VQA) on real-world document images in Bahasa Indone

INFORM-CT: INtegrating LLMs and VLMs FOR Incidental Findings Management in Abdominal CT

arXiv:2512.14732v2 Announce Type: replace-cross Abstract: Incidental findings in CT scans, though often benign, can have significant clinical implications and should be reported following established

INST-Align: Implicit Neural Alignment for Spatial Transcriptomics via Canonical Expression Fields

arXiv:2604.12084v1 Announce Type: new Abstract: Spatial transcriptomics (ST) measures mRNA expression while preserving spatial organization, but multi-slice analysis faces two coupled difficulties: la

Intelligent ROI-Based Vehicle Counting Framework for Automated Traffic Monitoring

arXiv:2604.12470v1 Announce Type: new Abstract: Accurate vehicle counting through video surveillance is crucial for efficient traffic management. However, achieving high counting accuracy while ensuri

Invariant Features for Global Crop Type Classification

arXiv:2509.03497v3 Announce Type: replace Abstract: Accurate global crop type mapping supports agricultural monitoring and food security, yet remains limited by the scarcity of labeled data in many re

Inverse Design of Inorganic Compounds with Generative AI

arXiv:2604.11827v1 Announce Type: cross Abstract: Machine learning is revolutionizing chemistry. Beyond the value of predictive models accelerating virtual screening, generative AI aims at enabling in

Is Vibe Coding the Future? An Empirical Assessment of LLM Generated Codes for Construction Safety

arXiv:2604.12311v1 Announce Type: cross Abstract: The emergence of vibe coding, a paradigm where non-technical users instruct Large Language Models (LLMs) to generate executable codes via natural lang

iTeach: In the Wild Interactive Teaching for Failure-Driven Adaptation of Robot Perception

model-releasesarxiv-cs-ro

arXiv:2410.09072v4 Announce Type: replace Abstract: Robotic perception models often fail when deployed in real-world environments due to out-of-distribution conditions such as clutter, occlusion, and

KCLarity at SemEval-2026 Task 6: Encoder and Zero-Shot Approaches to Political Evasion Detection

model-releasesarxiv-cs-cl

arXiv:2603.06552v2 Announce Type: replace Abstract: This paper describes the KCLarity team's participation in CLARITY, a shared task at SemEval 2026 on classifying ambiguity and evasion techniques in

KG-Hopper: Empowering Compact Open LLMs with Knowledge Graph Reasoning via Reinforcement Learning

arXiv:2603.21440v4 Announce Type: replace-cross Abstract: Large Language Models (LLMs) demonstrate impressive natural language capabilities but often struggle with knowledge-intensive reasoning tasks.

KnowRL: Boosting LLM Reasoning via Reinforcement Learning with Minimal-Sufficient Knowledge Guidance

arXiv:2604.12627v1 Announce Type: new Abstract: RLVR improves reasoning in large language models, but its effectiveness is often limited by severe reward sparsity on hard problems. Recent hint-based R

KumoRFM-2: Scaling Foundation Models for Relational Learning

arXiv:2604.12596v1 Announce Type: cross Abstract: We introduce KumoRFM-2, the next iteration of a pre-trained foundation model for relational data. KumoRFM-2 supports in-context learning as well as fi

Large Language Models are Powerful Electronic Health Record Encoders

arXiv:2502.17403v5 Announce Type: replace-cross Abstract: Electronic Health Records (EHRs) offer considerable potential for clinical prediction, but their complexity and heterogeneity challenge tradit

LASA: Language-Agnostic Semantic Alignment at the Semantic Bottleneck for LLM Safety

arXiv:2604.12710v1 Announce Type: cross Abstract: Large language models (LLMs) often demonstrate strong safety performance in high-resource languages, yet exhibit severe vulnerabilities when queried i

Latent Chain-of-Thought World Modeling for End-to-End Driving

arXiv:2512.10226v2 Announce Type: replace Abstract: Recent Vision-Language-Action (VLA) models for autonomous driving explore inference-time reasoning as a way to improve driving performance and safet

Latent Planning Emerges with Scale

arXiv:2604.12493v1 Announce Type: cross Abstract: LLMs can perform seemingly planning-intensive tasks, like writing coherent stories or functioning code, without explicitly verbalizing a plan; however

LaV-CoT: Language-Aware Visual CoT with Multi-Aspect Reward Optimization for Real-World Multilingual VQA

arXiv:2509.10026v4 Announce Type: replace Abstract: As large vision language models (VLMs) advance, their capabilities in multilingual visual question answering (mVQA) have significantly improved. Cha

League of LLMs: A Benchmark-Free Paradigm for Mutual Evaluation of Large Language Models

arXiv:2507.22359v4 Announce Type: replace Abstract: Although large language models (LLMs) have shown exceptional capabilities across a wide range of tasks, reliable evaluation remains a critical chall

Leveraging Weighted Syntactic and Semantic Context Assessment Summary (wSSAS) Towards Text Categorization Using LLMs

arXiv:2604.12049v1 Announce Type: cross Abstract: The use of Large Language Models (LLMs) for reliable, enterprise-grade analytics such as text categorization is often hindered by the stochastic natur

Lit2Vec: A Reproducible Workflow for Building a Legally Screened Chemistry Corpus from S2ORC for Downstream Retrieval and Text Mining

arXiv:2604.12498v1 Announce Type: cross Abstract: We present Lit2Vec, a reproducible workflow for constructing and validating a chemistry corpus from the Semantic Scholar Open Research Corpus using co

LLM-Enhanced Log Anomaly Detection: A Comprehensive Benchmark of Large Language Models for Automated System Diagnostics

arXiv:2604.12218v1 Announce Type: new Abstract: System log anomaly detection is critical for maintaining the reliability of large-scale software systems, yet traditional methods struggle with the hete

LLM-Guided Prompt Evolution for Password Guessing

arXiv:2604.12601v1 Announce Type: cross Abstract: Passwords still remain a dominant authentication method, yet their security is routinely subverted by predictable user choices and large-scale credent

Long-Horizon Plan Execution in Large Tool Spaces through Entropy-Guided Branching

arXiv:2604.12126v1 Announce Type: new Abstract: Large Language Models (LLMs) have significantly advanced tool-augmented agents, enabling autonomous reasoning via API interactions. However, executing m

M3D-Stereo: A Multiple-Medium and Multiple-Degradation Dataset for Stereo Image Restoration

arXiv:2604.12917v1 Announce Type: new Abstract: Image restoration under adverse conditions, such as underwater, haze or fog, and low-light environments, remains a highly challenging problem due to com

MedConcept: Unsupervised Concept Discovery for Interpretability in Medical VLMs

arXiv:2604.11868v1 Announce Type: new Abstract: While medical Vision-Language models (VLMs) achieve strong performance on tasks such as tumor or organ segmentation and diagnosis prediction, their opaq

Mema: Memory-Augmented Adapter for Enhanced Vision-Language Understanding

arXiv:2603.00655v2 Announce Type: replace Abstract: Multimodal Large Language Models (MLLMs) have achieved remarkable performance by aligning pretrained visual representations with the linguistic know

Memory as Metabolism: A Design for Companion Knowledge Systems

arXiv:2604.12034v1 Announce Type: new Abstract: Retrieval-Augmented Generation remains the dominant pattern for giving LLMs persistent memory, but a visible cluster of personal wiki-style memory archi

Mining Large Language Models for Low-Resource Language Data: Comparing Elicitation Strategies for Hausa and Fongbe

arXiv:2604.12477v1 Announce Type: cross Abstract: Large language models (LLMs) are trained on data contributed by low-resource language communities, yet the linguistic knowledge encoded in these model

MISID: A Multimodal Multi-turn Dataset for Complex Intent Recognition in Strategic Deception Games

arXiv:2604.12700v1 Announce Type: new Abstract: Understanding human intent in complex multi-turn interactions remains a fundamental challenge in human-computer interaction and behavioral analysis. Whi

Mitigating Shortcut Learning via Feature Disentanglement in Medical Imaging: A Benchmark Study

arXiv:2602.18502v2 Announce Type: replace Abstract: Although deep learning models in medical imaging often achieve excellent classification performance, they can rely on shortcut learning, exploiting

Mixed-Density Diffuser: Efficient Planning with Non-Uniform Temporal Resolution

arXiv:2510.23026v5 Announce Type: replace Abstract: Recent studies demonstrate that diffusion planners benefit from sparse-step planning over single-step planning. Training models to skip steps in the

Mobile GUI Agents under Real-world Threats: Are We There Yet?

arXiv:2507.04227v2 Announce Type: replace-cross Abstract: Recent years have witnessed a rapid development of mobile GUI agents powered by large language models (LLMs), which can autonomously execute d

Modality-Agnostic Prompt Learning for Multi-Modal Camouflaged Object Detection

arXiv:2604.12380v1 Announce Type: new Abstract: Camouflaged Object Detection (COD) aims to segment objects that blend seamlessly into complex backgrounds, with growing interest in exploiting additiona

Modality-Native Routing in Agent-to-Agent Networks: A Multimodal A2A Protocol Extension

arXiv:2604.12213v1 Announce Type: new Abstract: Preserving multimodal signals across agent boundaries is necessary for accurate cross-modal reasoning, but it is not sufficient. We show that modality-n

Monte Carlo Stochastic Depth for Uncertainty Estimation in Deep Learning

arXiv:2604.12719v1 Announce Type: new Abstract: The deployment of deep neural networks in safety-critical systems necessitates reliable and efficient uncertainty quantification (UQ). A practical and w

MoshiRAG: Asynchronous Knowledge Retrieval for Full-Duplex Speech Language Models

model-releasesarxiv-cs-cl

arXiv:2604.12928v1 Announce Type: new Abstract: Speech-to-speech language models have recently emerged to enhance the naturalness of conversational AI. In particular, full-duplex models are distinguis

Multi-Head Residual-Gated DeepONet for Coherent Nonlinear Wave Dynamics

arXiv:2604.11972v1 Announce Type: new Abstract: Coherent nonlinear wave dynamics are often strongly shaped by a compact set of physically meaningful descriptors of the initial state. Traditional neura

MVAdapt: Zero-Shot Multi-Vehicle Adaptation for End-to-End Autonomous Driving

arXiv:2604.11854v1 Announce Type: cross Abstract: End-to-End (E2E) autonomous driving models are usually trained and evaluated with a fixed ego-vehicle, even though their driving policy is implicitly

Narrative-Driven Paper-to-Slide Generation via ArcDeck

arXiv:2604.11969v1 Announce Type: new Abstract: We introduce ArcDeck, a multi-agent framework that formulates paper-to-slide generation as a structured narrative reconstruction task. Unlike existing m

Narrative over Numbers: The Identifiable Victim Effect and its Amplification Under Alignment and Reasoning in Large Language Models

arXiv:2604.12076v1 Announce Type: cross Abstract: The Identifiable Victim Effect (IVE) - the tendency to allocate greater resources to a specific, narratively described victim than to a statistically

Nemotron 3 Super: Open, Efficient Mixture-of-Experts Hybrid Mamba-Transformer Model for Agentic Reasoning

arXiv:2604.12374v1 Announce Type: cross Abstract: We describe the pre-training, post-training, and quantization of Nemotron 3 Super, a 120 billion (active 12 billion) parameter hybrid Mamba-Attention

NeuroPareto: Calibrated Acquisition for Costly Many-Goal Search in Vast Parameter Spaces

arXiv:2602.03901v4 Announce Type: replace Abstract: The pursuit of optimal trade-offs in high-dimensional search spaces under stringent computational constraints poses a fundamental challenge for cont