Search: “models”

Omni2Sound: Towards Unified Video-Text-to-Audio Generation

arXiv:2601.02731v3 Announce Type: replace-cross Abstract: Training a unified model integrating video-to-audio (V2A), text-to-audio (T2A), and joint video-text-to-audio (VT2A) generation offers signifi

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Perception Test 2025: Challenge Summary and a Unified VQA Extension

DGX agent

arXiv:2601.06287v2 Announce Type: replace Abstract: The Third Perception Test challenge was organised as a full-day workshop alongside the IEEE/CVF International Conference on Computer Vision (ICCV) 2

model-releasesarxiv-cs-cv

30 Apr 2026

Safety Is Not Universal: The Selective Safety Trap in LLM Alignment

arXiv:2601.04389v2 Announce Type: replace-cross Abstract: Current safety evaluations of large language models (LLMs) create a dangerous illusion of universal protection by aggregating harms under gene

SWE-Edit: Rethinking Code Editing for Efficient SWE-Agent

arXiv:2604.26102v1 Announce Type: cross Abstract: Large language model agents have achieved remarkable progress on software engineering tasks, yet current approaches suffer from a fundamental context

This startup’s new mechanistic interpretability tool lets you debug LLMs

model-releasesmit-tech-review

The San Francisco–based startup Goodfire just released a new tool, called Silico, that lets researchers and engineers peer inside an AI model and adjust its parameters—the settings that determine a mo

Agent-Diff: Benchmarking LLM Agents on Enterprise API Tasks via Code Execution with State-Diff-Based Evaluation

arXiv:2602.11224v3 Announce Type: replace-cross Abstract: We present Agent-Diff, a novel benchmarking framework for evaluating agentic Large Language Models (LLMs) on real-world productivity software

Align then Adapt: Rethinking Parameter-Efficient Transfer Learning in 4D Perception

arXiv:2602.23069v2 Announce Type: replace Abstract: Point cloud video understanding is critical for robotics as it accurately encodes motion and scene interaction. We recognize that 4D datasets are fa

Analyzing LLM Reasoning to Uncover Mental Health Stigma

arXiv:2604.25053v1 Announce Type: new Abstract: While large language models (LLMs) are increasingly being explored for mental health applications, recent studies reveal that they can exhibit stigma to

AQUA-Bench: Beyond Finding Answers to Knowing When There Are None in Audio Question Answering

arXiv:2601.12248v2 Announce Type: replace-cross Abstract: Recent advances in audio-aware large language models have shown strong performance on audio question answering. However, existing benchmarks m

Architecture Determines Observability in Transformers

arXiv:2604.24801v1 Announce Type: new Abstract: Autoregressive transformers make confident errors, but activation monitoring can catch them only if the model preserves an internal signal that output c

Cross-Lingual Jailbreak Detection via Semantic Codebooks

arXiv:2604.25716v1 Announce Type: new Abstract: Safety mechanisms for large language models (LLMs) remain predominantly English-centric, creating systematic vulnerabilities in multilingual deployment.

Genie Sim 3.0 : A High-Fidelity Comprehensive Simulation Platform for Humanoid Robot

model-releasesarxiv-cs-ro

arXiv:2601.02078v2 Announce Type: replace Abstract: The development of robust and generalizable robot learning models is critically contingent upon the availability of large-scale, diverse training da

HuM-Eval: A Coarse-to-Fine Framework for Human-Centric Video Evaluation

arXiv:2604.25361v1 Announce Type: new Abstract: Video generation models have developed rapidly in recent years, where generating natural human motion plays a pivotal role. However, accurately evaluati

Investigation into In-Context Learning Capabilities of Transformers

arXiv:2604.25858v1 Announce Type: new Abstract: Transformers have demonstrated a strong ability for in-context learning (ICL), enabling models to solve previously unseen tasks using only example input

Applications

Is the Modality Gap a Bug or a Feature? A Robustness Perspective

arXiv:2603.29080v2 Announce Type: replace Abstract: Many modern multi-modal models (e.g. CLIP) seek an embedding space in which the two modalities are aligned. Somewhat surprisingly, almost all existi

applicationsarxiv-cs-cv

Local Ai

Luminol-AIDetect: Fast Zero-shot Machine-Generated Text Detection based on Perplexity under Text Shuffling

arXiv:2604.25860v1 Announce Type: new Abstract: Machine-generated text (MGT) detection requires identifying structurally invariant signals across generation models, rather than relying on model-specif

local-aiarxiv-cs-cl

M^3-VQA: A Benchmark for Multimodal, Multi-Entity, Multi-Hop Visual Question Answering

arXiv:2604.25122v1 Announce Type: new Abstract: We present M^3-VQA, a novel knowledge-based Visual Question Answering (VQA) benchmark, to enhance the evaluation of multimodal large language models (ML

Magnification-Invariant Image Classification via Domain Generalization and Stable Sparse Embedding Signatures

arXiv:2604.25817v1 Announce Type: new Abstract: Magnification shift is a major obstacle to robust histopathology classification, because models trained on one imaging scale often generalize poorly to

researcharxiv-cs-cv

Mitigating Coordinate Prediction Bias from Positional Encoding Failures

arXiv:2510.22102v2 Announce Type: replace-cross Abstract: While Multimodal Large Language Models (MLLMs) excel at general vision-language tasks, precise coordinate prediction remains a significant cha

Local Ai

MobileLLM-Flash: Latency-Guided On-Device LLM Design for Industry Scale Deployment

arXiv:2603.15954v2 Announce Type: replace Abstract: Real-time AI experiences call for on-device large language models (OD-LLMs) optimized for efficient deployment on resource-constrained hardware. The

local-aiarxiv-cs-lg

Nemotron 3 Nano Omni: Efficient and Open Multimodal Intelligence

arXiv:2604.24954v1 Announce Type: cross Abstract: We introduce Nemotron 3 Nano Omni, the latest model in the Nemotron multimodal series and the first to natively support audio inputs alongside text, i

Odysseys: Benchmarking Web Agents on Realistic Long Horizon Tasks

arXiv:2604.24964v1 Announce Type: cross Abstract: Existing web agent benchmarks have largely converged on short, single-site tasks that frontier models are approaching saturation on. However, real wor

PLMGH: What Matters in PLM-GNN Hybrids for Code Classification and Vulnerability Detection

arXiv:2604.25599v1 Announce Type: cross Abstract: Code understanding models increasingly rely on pretrained language models (PLMs) and graph neural networks (GNNs), which capture complementary semanti

researcharxiv-cs-lg

Tools

Qwen3.6-Plus is now available on Together AI Try it now: http://www.together.ai/models/qwen36-plus

Qwen3.6-Plus, a large language model, is now available for use through Together AI's platform. Together AI has announced the availability of this model and is inviting users to try it via their models

toolstogether-ai--x

RbtAct: Rebuttal as Supervision for Actionable Review Feedback Generation

arXiv:2603.09723v2 Announce Type: replace Abstract: Large language models (LLMs) are increasingly used across the scientific workflow, including to draft peer-review reports. However, many AI-generate

Applications

RELIC: Evaluating Complex Reasoning via the Recognition of Languages In-Context

arXiv:2506.05205v2 Announce Type: replace Abstract: Large language models (LLMs) are increasingly used to solve complex tasks where they must retrieve and compose many pieces of in-context information

applicationsarxiv-cs-cl

SIEVES: Selective Prediction Generalizes through Visual Evidence Scoring

arXiv:2604.25855v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) achieve ever-stronger performance on visual-language tasks. Even as traditional visual question answering bench

SynMotion: Semantic-Visual Adaptation for Motion Customized Video Generation

arXiv:2506.23690v2 Announce Type: replace Abstract: Diffusion-based video motion customization facilitates the acquisition of human motion representations from a few video samples, while achieving arb

The founder’s AI foundation: The top announcements for startups from Next ‘26

model-releasesgoogle-cloud-ai

The momentum is undeniable: the world’s fastest-growing AI startups are building with Google Cloud. Instead of stitching together fragmented point solutions, founders are building their businesses her

Towards Unified Multi-task EEG Analysis with Low-Rank Adaptation

arXiv:2604.25131v1 Announce Type: new Abstract: Recent self-supervised pre-training methods for electroencephalogram (EEG) have shown promising results. However, the pre-trained models typically requi

Tutorials

2D Pre-Training for 3D Pose Estimation

arXiv:2604.22830v1 Announce Type: new Abstract: Pre-training is a general method that is used in a range of deep learning tasks. By first training a model on one task, and then further training on the

tutorialsarxiv-cs-cv

A BERTology View of LLM Orchestrations: Token- and Layer-Selective Probes for Efficient Single-Pass Classification

arXiv:2601.13288v2 Announce Type: replace Abstract: Production LLM systems often rely on separate models for safety and other classification-heavy steps, increasing latency, VRAM footprint, and operat

A Parametric Memory Head for Continual Generative Retrieval

arXiv:2604.23388v1 Announce Type: cross Abstract: Generative information retrieval (GenIR) consolidates retrieval into a single neural model that decodes document identifiers (docids) directly from qu

Accelerating Quantum Materials Characterization: Hybrid Active Learning for Autonomous Spin Wave Spectroscopy

arXiv:2604.23821v1 Announce Type: cross Abstract: Autonomous neutron spectroscopy must solve three distinct tasks: detection (where is the signal?), inference (which Hamiltonian governs it?), and refi

All That Glitters Is Not Audio: Rethinking Text Priors and Audio Reliance in Audio-Language Evaluation

arXiv:2604.24401v1 Announce Type: cross Abstract: Large Audio-Language Models show consistent performance gains across speech and audio benchmarks, yet high scores may not reflect true auditory percep

Always Tell Me The Odds: Fine-grained Conditional Probability Estimation

arXiv:2505.01595v2 Announce Type: replace-cross Abstract: We present a state-of-the-art model for fine-grained probability estimation of propositions conditioned on context. Recent advances in large l

researcharxiv-cs-ai

Applications of the Transformer Architecture in AI-Assisted English Reading Comprehension

arXiv:2604.23615v1 Announce Type: cross Abstract: This paper studies interpretable and fair artificial intelligence architectures for understanding English reading. Introduced transformer-based models

AutoGUI-v2: A Comprehensive Multi-Modal GUI Functionality Understanding Benchmark

arXiv:2604.24441v1 Announce Type: new Abstract: Autonomous agents capable of navigating Graphical User Interfaces (GUIs) hold the potential to revolutionize digital productivity. However, achieving tr

Tutorials

AV-Master: Dual-Path Comprehensive Perception Makes Better Audio-Visual Question Answering

arXiv:2510.18346v2 Announce Type: replace Abstract: Audio-Visual Question Answering (AVQA) requires models to effectively utilize both visual and auditory modalities to answer complex and diverse ques

tutorialsarxiv-cs-cv

Benchmarking Testing in Automated Theorem Proving

arXiv:2604.23698v1 Announce Type: new Abstract: Recent advances in large language models (LLMs) have shown promise in formal theorem proving, yet evaluating semantic correctness remains challenging. E

BrickNet: Graph-Backed Generative Brick Assembly

arXiv:2604.22984v1 Announce Type: new Abstract: We train a language model to generate LEGO-brick build sequences. While prior work has been restricted to discrete, voxel-like towers, we consider a muc

researcharxiv-cs-cv

Complexity of Linear Regions in Self-supervised Deep ReLU Networks

arXiv:2604.24393v1 Announce Type: cross Abstract: There has been growing interest in studying the complexity of Rectified Linear Unit (ReLU) based activation networks. Recent work investigates the evo

CRISP: Persistent Concept Unlearning via Sparse Autoencoders

arXiv:2508.13650v3 Announce Type: replace Abstract: As large language models (LLMs) are increasingly deployed in real-world applications, the need to selectively remove unwanted knowledge while preser

Defective Task Descriptions in LLM-Based Code Generation: Detection and Analysis

arXiv:2604.24703v1 Announce Type: cross Abstract: Large language models are widely used for code generation, yet they rely on an implicit assumption that the task descriptions are sufficiently detaile

Tutorials

Doloris: Dual Conditional Diffusion Implicit Bridges with Sparsity Masking Strategy for Unpaired Single-Cell Perturbation Estimation

arXiv:2506.21107v3 Announce Type: replace Abstract: Estimating single-cell responses across various perturbations facilitates the identification of key genes and enhances drug screening, significantly

tutorialsarxiv-cs-lg

EPM-RL: Reinforcement Learning for On-Premise Product Mapping in E-Commerce

arXiv:2604.23993v1 Announce Type: cross Abstract: Product mapping, the task of deciding whether two e-commerce listings refer to the same product, is a core problem for price monitoring and channel vi

Global Context or Local Detail? Adaptive Visual Grounding for Hallucination Mitigation

arXiv:2604.24396v1 Announce Type: cross Abstract: Vision-Language Models (VLMs) are frequently undermined by object hallucination--generating content that contradicts visual reality--due to an over-re

Local Ai

Kwai Summary Attention Technical Report

arXiv:2604.24432v1 Announce Type: cross Abstract: Long-context ability, has become one of the most important iteration direction of next-generation Large Language Models, particularly in semantic unde

local-aiarxiv-cs-ai