Search: “model-releases”

GREAT: Generalizable Backdoor Attacks in RLHF via Emotion-Aware Trigger Synthesis

arXiv:2510.09260v2 Announce Type: replace-cross Abstract: Recent work has shown that RLHF is highly susceptible to backdoor attacks. However, existing methods often rely on rare tokens or fixed trigge

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Model Releases

GuidaPA: Privacy-Preserving Chatbot for Public Administration via Federated Learning

DGX agent

arXiv:2606.01386v1 Announce Type: new Abstract: We present GuidaPA, a privacy-preserving chatbot for the Italian Public Administration (PA) trained via Federated Learning (FL) on documentation from tw

model-releasesarxiv-cs-ai

2 Jun 2026

HAIM: Human-AI Music Datasets for AI Music Production Tracking Benchmark

arXiv:2606.01686v1 Announce Type: cross Abstract: As generative platforms such as Suno and Udio reach human-grade audio quality, the scope of AI's utility has expanded across the entire music producti

HakushoBench: A Japanese Chart and Table VQA Benchmark from Governmental White Papers

arXiv:2606.01132v1 Announce Type: new Abstract: Understanding chart and table images is essential for applying vision-language models (VLMs) to real-world document understanding. While English benchma

HalleluBERT: Let Every Token That Has Meaning Bear Its Weight

arXiv:2510.21372v2 Announce Type: replace Abstract: Transformer-based models have advanced NLP, yet Hebrew still lacks a RoBERTa encoder that is trained at scale and released in both base and large va

HALO: Learning Human-Robot Collaboration via Heterogeneous-Agent Lyapunov Policy Optimization

arXiv:2603.03741v2 Announce Type: replace-cross Abstract: To improve generalization and resilience in human-robot collaboration (HRC), robots must contend with diverse combinations of human behaviors

HERO'S JOURNEY: Testing Complex Rule Induction with Text Games

arXiv:2606.02556v1 Announce Type: new Abstract: We introduce HERO'S JOURNEY, a benchmark for rule induction in goal-directed episodic tasks, where agents must infer hidden rules from demonstrations an

Hierarchical Online Prompt Mutation with Dual-Loop Feedback for Guardrailed Evidence Document Generation: A Production-Evaluation Case Study

arXiv:2606.01472v1 Announce Type: cross Abstract: High-stakes production document-generation systems require language models to be adaptive, evidence-grounded, and auditable. We present HOPM, a hierar

Hierarchically Decoupled Mixture-of-Experts for Robust Traffic Sign Recognition in Complex Driving Scenarios

arXiv:2606.01822v1 Announce Type: new Abstract: Traffic sign detection is a fundamental component of environmental perception in autonomous driving and intelligent transportation systems. However, mos

HLL: Can Agents Cross Humanity's Last Line of Verification?

arXiv:2606.02449v1 Announce Type: new Abstract: Multimodal agents are increasingly expected to operate interfaces on behalf of users, raising a central deployment question: can they truly substitute f

HomeFlow: A Data Flywheel for Smart Home Agent Training with Verifiable Simulation

arXiv:2606.01230v1 Announce Type: new Abstract: Large language model agents are moving beyond text-only interaction toward physical-world control, with smart homes as a representative domain. Real dom

How AI Fails: An Interactive Pedagogical Tool for Demonstrating Dialectal Bias in Automated Toxicity Models

arXiv:2511.06676v3 Announce Type: replace Abstract: Now that AI-driven moderation has become pervasive in everyday life, we often hear claims that 'the AI is biased'. While this is often said jokingly

How to Correctly Report LLM-as-a-Judge Evaluations

arXiv:2511.21140v4 Announce Type: replace-cross Abstract: Large language models (LLMs) are widely used as scalable evaluators of model responses in lieu of human annotators. However, imperfect sensiti

HR-VILAGE-3K3M: A Human Respiratory Viral Immunization Longitudinal Gene Expression Dataset for Systems Immunity

arXiv:2505.14725v2 Announce Type: replace-cross Abstract: Respiratory viral infections pose a global health burden, yet the cellular immune mechanisms underlying protection and pathology remain unclea

Hybrid Imbalanced Regression Through Unified Data-Level and Algorithm-Level Balancing

arXiv:2606.01221v1 Announce Type: cross Abstract: Imbalanced learning is a critical challenge in machine learning, where underrepresented target values can bias models and degrade prediction performan

Hybrid Verified Decoding: Learning to Allocate Verification in Speculative Decoding

arXiv:2606.01019v1 Announce Type: cross Abstract: Large Language Model (LLM) generation remains expensive because autoregressive decoding calls the model once for each new token. Speculative decoding

Hyperspherical Variational Autoencoders Using Efficient Spherical Cauchy Distribution

arXiv:2506.21278v3 Announce Type: replace-cross Abstract: We propose spherical Cauchy (spCauchy) latent variables for variational autoencoders on hyperspherical latent spaces. The spCauchy family has

HypothesisMed: Inference-Time Answer Fusion and Structured Hypothesis-Space Reporting for Biomedical Question Answering

arXiv:2606.00971v1 Announce Type: new Abstract: Biomedical question answering with large language models is commonly evaluated using answer accuracy, but answer accuracy alone does not indicate whethe

hZACH-ViT: Curved Latent Geometry for Compact Vision Transformers in Low-Data Medical Imaging

arXiv:2606.00906v1 Announce Type: new Abstract: Compact Vision Transformers are attractive for medical imaging in low-data and resource-constrained settings, but most existing variants assume that Euc

'I Strongly Suspect This Website Is a Scam': Benchmarking PII Leakage and Detection without Defense in Autonomous Web Agents

arXiv:2606.00497v1 Announce Type: cross Abstract: Deceptive web content, widely instantiated across the internet and commonly known as extit{social-engineering attacks}, manipulates autonomous web age

I-WebGenBench : Evaluating Interactivity in LLM-Generated Scientific Web Applications

arXiv:2606.00750v1 Announce Type: new Abstract: Recent advances in visual language models have enabled autonomous agents for complex reasoning, tool use, and document understanding. However, existing

Identifying High-Confidence Social Biases in LLMs for Trustworthy Conversational Tutoring Agents

arXiv:2606.01584v1 Announce Type: cross Abstract: Conversational tutoring agents have been shown to improve learning engagement and student outcomes, and large language models (LLMs) are increasingly

IMAC-AgriVLN: Can Agricultural Vision-and-Language Navigation Agents be Aware of Instruction Mistakes?

model-releasesarxiv-cs-ro

arXiv:2606.02519v1 Announce Type: new Abstract: Agricultural robots are serving as powerful assistants across a wide range of agricultural tasks, nevertheless, still heavily relying on manual operatio

Implicit Geographic Inference in LLM Medical Triage: Language-Driven Disparities in Emergency Recommendations

arXiv:2606.01204v1 Announce Type: cross Abstract: We investigate whether large language models produce different medical triage recommendations for identical symptoms based solely on the language of t

Implicit Regularization for Multi-label Feature Selection

arXiv:2411.11436v2 Announce Type: replace-cross Abstract: In this paper, we address the problem of feature selection in the context of multi-label learning, by using a new estimator based on implicit

IndoBias: A Dual Track Culturally Grounded Benchmark for LLMs Bias Evaluation in Indonesian Languages

arXiv:2606.01260v1 Announce Type: cross Abstract: Despite being home to more than 1300 ethnic groups and 700 indigenous languages, bias in Large Language Models has not been fully studied in Indonesia

InPhyRe Discovers: Large Multimodal Models Struggle in Inductive Physical Reasoning

arXiv:2509.12263v3 Announce Type: replace Abstract: Large multimodal models (LMMs) encode physical laws observed during training, such as momentum conservation, as parametric knowledge. It allows LMMs

InsightVQA: High-Dimensional Emotion-Cognitive Visual Question Answering Benchmark

arXiv:2606.02171v1 Announce Type: new Abstract: Visual emotion understanding requires models not only to recognize emotional states, but also to why they arise and perform higher-level cognitive reaso

InstructSAM: Segment Any Instance with Any Instructions

arXiv:2605.26102v2 Announce Type: replace Abstract: In this paper, we introduce InstructSAM, a unified and streamlined framework designed for multi-instance segmentation under arbitrary instructions.

IntraShuffler: A Privacy Preserving Framework for Heterogeneous DP Federated Learning

arXiv:2606.02563v1 Announce Type: new Abstract: Heterogeneous Differential Privacy (HDP) in Federated Learning (FL) allows clients to select individual privacy budgets (arepsilon_i) according to insti

Investigating and Alleviating Harm Amplification in LLM Interactions

arXiv:2606.02423v1 Announce Type: new Abstract: Large language models (LLMs) can serve as helpful assistants, yet they can equally function as harm amplifiers that enable malicious users to achieve ha

'I've Seen How This Goes': Characterizing Diversity via Progressive Conditional Surprise

arXiv:2606.01811v1 Announce Type: cross Abstract: Measuring the diversity of creative outputs is central to evaluating post-training mode collapse, comparing decoding strategies, and quantifying creat

JenBridge: Adaptive Long-Form Video Soundtracking across Scene Transitions

arXiv:2606.01703v1 Announce Type: cross Abstract: We address the challenge of generating high-fidelity, long-form soundtracks that remain coherent across scene transitions. Existing AI music systems a

K-BrowseComp: A Web Browsing Agent Benchmark Grounded in Korean Contexts

arXiv:2606.02404v1 Announce Type: new Abstract: Frontier model evaluations are shifting from foundational capabilities (e.g., instruction following and reasoning) toward compositional, agentic ones, b

KliniskVestBERT: BERT Model Specialised to Norwegian Clinical Texts

arXiv:2606.01904v1 Announce Type: cross Abstract: The increasing application of Natural Language Processing (NLP) in healthcare demands language models specifically attuned to the complexities of clin

Knowledge-Intensive Video Generation

arXiv:2606.01285v1 Announce Type: cross Abstract: Text-to-video generation has advanced rapidly in visual quality, but remains under-evaluated for factuality and practical usefulness. We introduce kno

KnowledgeBerg: Evaluating Systematic Knowledge Coverage and Compositional Reasoning in Large Language Models

arXiv:2604.17621v2 Announce Type: replace Abstract: Many real-world questions appear deceptively simple yet implicitly demand two capabilities: (i) systematic coverage of a bounded knowledge universe

KromHC: Manifold-Constrained Hyper-Connections with Kronecker-Product Residual Matrices

arXiv:2601.21579v2 Announce Type: replace Abstract: The success of Hyper-Connections (HC) in neural networks (NN) has also highlighted issues related to training instability and restricted scalability

LALE: Lightweight-Transformer Architecture for Land-Cover Estimation

arXiv:2606.02092v1 Announce Type: cross Abstract: Semantic segmentation of remote sensing imagery requires models that capture both global context and local detail under tight computational budgets. P

Language-Native Materials Processing Design by Lightly Structured Text Database and Reasoning Large Language Model

arXiv:2509.06093v4 Announce Type: replace-cross Abstract: Materials synthesis procedures are predominantly documented as narrative text in papers, protocols, and laboratory records, placing them beyon

LAP: Fast LAtent Diffusion Planner for Autonomous Driving

model-releasesarxiv-cs-ro

arXiv:2512.00470v4 Announce Type: replace Abstract: Diffusion models have demonstrated strong capabilities for modeling human-like driving behaviors in autonomous driving, but their iterative sampling

Large Electron Model: A Universal Ground State Predictor

arXiv:2603.02346v2 Announce Type: replace-cross Abstract: We introduce Large Electron Model, a single neural network model that produces variational wavefunctions of interacting electrons over the ent

Large-scale Uncertainty Quantification for Latent Variable Models Using Subsampling Markov Chain Monte Carlo

arXiv:2606.00309v1 Announce Type: new Abstract: Stochastic gradient Langevin dynamics combined with Gibbs updates (SGLD--Gibbs) provides a highly scalable approach to approximate Bayesian inference in

LASER: Loss-Aware Singular-value Decomposition and Rank Allocation for Efficient Low-Precision Vision-Language Models

arXiv:2606.00573v1 Announce Type: new Abstract: Vision-language models (VLMs) deliver strong multimodal reasoning capabilities, but their large computational cost and high parameter counts make deploy

LaSR: Context-Aware Speech Recognition via Latent Reasoning

arXiv:2606.00507v1 Announce Type: new Abstract: Recent advances in Speech Large Language Models (Speech LLMs) have significantly enhanced spoken language understanding and reasoning. However, their co

LeAP: Learnable Adaptive Permutation for Feature Selection in Heterogeneous and Sparse Recommender Systems

arXiv:2606.01111v1 Announce Type: new Abstract: Modern industrial recommender systems rely on thousands of heterogeneous features -- ranging from low-dimensional scalars (e.g., statistical value) to h

Learning-based Directed Graph Abstraction of Combinatorial Spaces for Order-Preserving Search in Mixed-Combinatorial Nonlinear Optimization

arXiv:2606.01425v1 Announce Type: new Abstract: Mixed-combinatorial nonlinear programming (MCNLP) problems arise in many engineering design and planning applications, e.g., due to categorical, compone

Learning Implicit Bias in Generative Spaces for Accelerating Protein Dynamics Emulation

arXiv:2606.01833v1 Announce Type: cross Abstract: Generative emulators of protein dynamics produce plausible trajectories at a fraction of the cost of molecular dynamics, but they inherit their traini