Search: “model-releases”

IPO-Mine: A Toolkit and Dataset for Section-Structured Analysis of Long, Multimodal IPO Documents

arXiv:2605.28714v1 Announce Type: cross Abstract: An Initial Public Offering (IPO) filing is a document released when a private firm goes public, allowing individual (retail) investors to purchase its

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Model Releases

IRDS: Interpretable RLVR Data Selection via Verifier-Coupled Sparse Autoencoder Coverage

DGX agent

arXiv:2605.28247v1 Announce Type: cross Abstract: Reinforcement learning with verifiable rewards (RLVR) has become a key technique for en- hancing LLM reasoning, yet its data ineffi- ciency remains a

model-releasesarxiv-cs-ai

28 May 2026

Janus-LoRA: A Balanced Low-Rank Adaptation for Continual Learning

arXiv:2605.28495v1 Announce Type: new Abstract: Low-Rank Adaptation (LoRA) has emerged as a promising paradigm for Continual Learning. It independently updates its low-rank factors (A and B), creating

JMedEthicBench: A Multi-Turn Conversational Benchmark for Evaluating Medical Safety in Japanese Large Language Models

arXiv:2601.01627v3 Announce Type: replace-cross Abstract: As Large Language Models (LLMs) are increasingly deployed in healthcare field, it becomes essential to carefully evaluate their medical safety

KSAFE-MM: A Multimodal Safety Benchmark via Localized Contextualization for Korean Cultural Risks

arXiv:2605.28013v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) exacerbate safety risks by introducing vulnerabilities across multiple modalities, such as language and vision.

KVoiceBench, KOpenAudioBench, and KMMAU: Agent-Driven Korean Speech Benchmarks for Evaluating SpeechLMs

arXiv:2605.27984v1 Announce Type: cross Abstract: Speech language models (SpeechLMs) have achieved substantial progress by extending large language models (LLMs) to the speech modality. However, Speec

Laguna M.1/XS.2 Technical Report

arXiv:2605.27605v1 Announce Type: new Abstract: We present Laguna M.1 and Laguna XS.2, two Mixture-of-Experts foundation models built for long-horizon, agentic coding: M.1 has 225.8B total parameters

Law of Neural Interaction: Depth-Width Shape, Interaction Efficiency, and Generalization

arXiv:2605.27989v1 Announce Type: new Abstract: The guidance of scaling laws has increased the resource demands of modern large language models (LLMs), yet it remains questionable whether these models

LCO: LLM-based Constraint Optimization for Safer Agentic LLMs in Real-world Tasks

arXiv:2605.27375v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly acting as autonomous agents, but their continuous interaction with the environment can lead to in-context

Learning Compositional Latent Structure with Vector Networks

arXiv:2605.28007v1 Announce Type: cross Abstract: Deep networks are powerful function approximators, but they typically store many different computations in shared weight matrices, making it difficult

Learning to Translate from Soft to Hard LLM Prompts

arXiv:2605.27642v1 Announce Type: new Abstract: Soft prompt tuning is a parameter-efficient method for adapting LLMs to specific tasks, but suffers from a lack of interpretability. Building on recent

LEIA: Learned Environment for Interactive Architected Materials

arXiv:2605.28368v1 Announce Type: new Abstract: World models have enabled interactive exploration of game environments and robotic manipulation, but physical engineering remains beyond their reach: re

LESA: Learnable Stage-Aware Predictors for Diffusion Model Acceleration

arXiv:2602.20497v3 Announce Type: replace-cross Abstract: Diffusion models have achieved remarkable success in image and video generation tasks. However, the high computational demands of Diffusion Tr

Let the Results Speak: A Replication-First Paradigm for LLM Behavioral Benchmarking

arXiv:2605.27914v1 Announce Type: cross Abstract: Subjective evaluation of LLM behavior -- empathy, restraint, calibrated emotional tone -- is hard. Human inter-rater agreement on such qualities satur

LiveBrowseComp: Are Search Agents Searching, or Just Verifying What They Already Know?

arXiv:2605.28721v1 Announce Type: new Abstract: Are LLM-based search agents genuinely searching, or using the web to verify what they already know? We study this question on BrowseComp with three diag

LLM Zeroth-Order Fine-Tuning is an Inference Workload

arXiv:2605.28760v1 Announce Type: new Abstract: Zeroth-order (ZO) fine-tuning is attractive for large language models because it replaces backpropagation with forward objective evaluations. Existing i

Local MDI+: Local Feature Importances for Tree-Based Models

arXiv:2506.08928v2 Announce Type: replace Abstract: Tree-based ensembles such as random forests remain the go-to for tabular data over deep learning models due to their prediction performance and comp

LV-OSD: Language-Vision-Complementary Open-Set Object Detection

arXiv:2605.28271v1 Announce Type: new Abstract: Object detection is an important task in computer vision, which aims to detect the objects of interest. through the given category list or query images.

MACReD: A Multi-Agent Collaborative Reasoning Framework for Reaction Diagram Parsing

arXiv:2605.28077v1 Announce Type: new Abstract: Parsing chemical reaction diagrams from scientific literature is challenging due to heterogeneous layouts, intertwined visual elements, and the difficul

Mags-RL: Wearing Multimodal LLMs a Magnifying Glass via Agentic Reinforcement Learning For Complex Scene Reasoning

arXiv:2605.27960v1 Announce Type: new Abstract: Despite their popularity and success, Multimodal Large Language Models (MLLMs) often struggle to interpret images accurately, which limits their reasoni

Mahalanobis PatchCore: Covariance-Aware and Streaming-Compatible Industrial Anomaly Detection

arXiv:2605.27748v1 Announce Type: cross Abstract: Industrial visual anomaly detection is usually one-class: normal images are abundant, while defects are rare, heterogeneous, and often unavailable dur

MangaFlow: An End-to-End Agentic Framework for Controllable Story to Manga Generation

arXiv:2605.28173v1 Announce Type: new Abstract: End-to-end manga generation is a structured visual storytelling task that requires story decomposition, recurring character and scene grounding, page la

Many Dialects, Many Languages, One Cultural Lens: Evaluating Multilingual VLMs for Bengali Culture Understanding Across Historically Linked Languages and Regional Dialects

arXiv:2603.21165v2 Announce Type: replace Abstract: Bangla culture is richly expressed through region, dialect, history, food, politics, media, and everyday visual life, yet it remains underrepresente

MaskClaw: Edge-Side Personalized Privacy Arbitration for GUI Agents with Behavior-Driven Skill Evolution

arXiv:2605.28646v1 Announce Type: cross Abstract: GUI agents rely on screenshots to infer intent and operate across applications, but these screenshots often contain private messages, medical records,

MemCog: From Memory-as-Tool to Memory-as-Cognition in Conversational Agents

arXiv:2605.28046v1 Announce Type: new Abstract: Existing agent memory systems universally follow what we term a Memory-as-Tool paradigm where a single query triggers one-shot retrieval of flat passage

MemGuard: Preventing Memory Contamination in Long-Term Memory-Augmented Large Language Models

arXiv:2605.28009v1 Announce Type: cross Abstract: Memory-augmented large language models extend reasoning beyond a fixed context window by maintaining long-term memory across interactions. However, ex

MemTrace: Tracing and Attributing Errors in Large Language Model Memory Systems

arXiv:2605.28732v1 Announce Type: cross Abstract: Memory is essential for enabling large language models to support long-horizon reasoning, yet existing memory systems remain unreliable and difficult

MeniOmni: A Structured Multimodal Benchmark for Holistic Meniscus Injury Assessment

arXiv:2605.28161v1 Announce Type: new Abstract: Clinical diagnosis of meniscus injuries requires radiologists to integrate volumetric MRI evidence with patient context (e.g., sex, age, BMI) and to pro

Meta-Attention: Bayesian Per-Token Routing for Efficient Transformer Inference

arXiv:2605.28384v1 Announce Type: new Abstract: Standard transformer architectures apply a single attention mechanism uniformly across all tokens and sequence positions, irrespective of local context

MetaboT: An LLM-based Multi-Agent Frameworkfor Interactive Analysis of Mass SpectrometryMetabolomics Knowledge Graphs

arXiv:2510.01724v2 Announce Type: replace Abstract: Mass spectrometry-based metabolomics generates complex, high-dimensional data that holds vast potential for biological discovery but remains difficu

MIRA: A Bilingual Benchmark for Medical Information Response Audit

arXiv:2605.28025v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used to provide public-facing health information, yet existing safety evaluations overlook whether respons

MIRAGE: Context-Aware Prompt Injection against Mobile GUI Agents via User-Generated Content

arXiv:2605.28116v1 Announce Type: cross Abstract: Mobile graphical user interface (GUI) agents driven by vision-language models (VLMs) perceive the screen as rendered pixels and choose actions from wh

Mitigating Staleness in Asynchronous Pipeline Parallelism via Basis Rotation

arXiv:2602.03515v2 Announce Type: replace-cross Abstract: Asynchronous pipeline parallelism maximizes hardware utilization by eliminating the pipeline bubbles inherent in synchronous execution, offeri

MMTABREAL: Real-World Benchmark for Multimodal Table Understanding

arXiv:2505.21771v2 Announce Type: replace-cross Abstract: Multimodal tables i.e. tabular layouts interleaved with charts, maps, icons, and color encodings are ubiquitous in real applications yet remai

Models That Know How Evaluations Are Designed Score Safer

arXiv:2605.28591v1 Announce Type: cross Abstract: The validity of AI safety evaluations depends on models behaving consistently across controlled and deployment settings. Prior work has identified tes

MolLingo: Molecule-Native Representations for LLM-Powered Scientific Agents

arXiv:2605.27853v1 Announce Type: new Abstract: We present MolLingo, a multi-agent system that emulates the reasoning process of a chemist to automate molecular design. Existing LLM-based approaches e

Moment Matters: Mean and Variance Causal Graph Discovery from Heteroscedastic Observational Data

arXiv:2602.23602v2 Announce Type: replace-cross Abstract: Heteroscedasticity -- where the variance of a variable changes with other variables -- is pervasive in real data, and elucidating why it arise

MTAVG-Bench 2.0: Diagnosing Failure Modes of Cinematic Expressiveness in Multi-Talker Audio-Video Generation

arXiv:2605.28035v1 Announce Type: new Abstract: In recent years, Multi-Talker Audio-Video Generation (MTAVG) models have shown promising performance on fundamental metrics such as lip-sync and audio-v

Multi-Adapter Representation Interventions via Energy Calibration

arXiv:2605.28722v1 Announce Type: new Abstract: Representation intervention has emerged as a promising paradigm for aligning large language models toward desired behaviors without modifying model weig

MUSE: Benchmarking Manufacturable, Functional, and Assemblable Text-to-CAD Generation

arXiv:2605.28579v1 Announce Type: new Abstract: Large language models (LLMs) have recently advanced text-driven 3D generation, yet Text-to-CAD remains far from supporting industrial product design. Ex

NanoVDR: Distilling a 2B Vision-Language Retriever into a 70M Text-Only Encoder for Visual Document Retrieval

arXiv:2603.12824v2 Announce Type: replace-cross Abstract: Vision-Language Model (VLM) based retrievers have advanced visual document retrieval (VDR) to impressive quality. They require the same multi-

NL-MambaXCT: Self-Supervised Nested-Learning Mamba for Nomex Honeycomb X-ray CT Defect Classification

arXiv:2605.27454v1 Announce Type: cross Abstract: X-ray computed tomography (XCT) is widely used for non-destructive testing of Nomex honeycomb structures in aerospace manufacturing, but industrial in

Not All Pixels Are Equal: Pixel-wise Meta-Learning for Medical Segmentation with Noisy Labels

arXiv:2511.18894v5 Announce Type: replace-cross Abstract: Medical image segmentation is crucial for clinical applications, but it is frequently disrupted by noisy annotations and ambiguous anatomical

OccuReward: LLM-Guided Occupant-Centric Reward Shaping for Demographic Equity in Grid-Interactive Buildings

arXiv:2605.28168v1 Announce Type: new Abstract: Large language models (LLMs) have demonstrated promising capability in generating reward functions for deep reinforcement learning (DRL)-based building

{Omega}-QVLA: Robust Quantization for Vision-Language-Action Models via Composite Rotation and Per-step Scaling

arXiv:2605.28803v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models unify perception, reasoning, and control within a single policy, yet their multi-billion-parameter backbones and dif

On Compositional Learning Behaviours in Formal Mathematics

arXiv:2605.28512v1 Announce Type: new Abstract: Self-evolving scientific agents capable of conquering the hard tail of formal mathematics require Compositional Learning Behaviours (CLBs) -- the capaci

On the Equivariant Learning of the Q-tensor Order Parameter

arXiv:2605.27679v1 Announce Type: cross Abstract: We construct and evaluate group-equivariant neural networks for the prediction of the two-dimensional Q-tensor order parameter of nematic liquid cryst

On the Intrinsic Limits of Transformer Image Embeddings in Non-Solvable Spatial Reasoning

arXiv:2601.03048v2 Announce Type: replace-cross Abstract: Vision Transformers (ViTs) excel in semantic recognition but exhibit systematic failures in spatial reasoning tasks such as mental rotation. W