Search: “model-releases”

UniEditBench: A Unified and Cost-Effective Benchmark for Image and Video Editing via Distilled MLLMs

arXiv:2604.15871v1 Announce Type: cross Abstract: The evaluation of visual editing models remains fragmented across methods and modalities. Existing benchmarks are often tailored to specific paradigms

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Model Releases

VEFX-Bench: A Holistic Benchmark for Generic Video Editing and Visual Effects

DGX agent

arXiv:2604.16272v1 Announce Type: cross Abstract: As AI-assisted video creation becomes increasingly practical, instruction-guided video editing has become essential for refining generated or captured

model-releasesarxiv-cs-ai

20 Apr 2026

vla-eval: A Unified Evaluation Harness for Vision-Language-Action Models

arXiv:2603.13966v2 Announce Type: replace Abstract: Vision-Language-Action (VLA) models are increasingly evaluated across multiple simulation benchmarks, yet adding each benchmark to an evaluation pip

VLegal-Bench: Cognitively Grounded Benchmark for Vietnamese Legal Reasoning of Large Language Models

arXiv:2512.14554v5 Announce Type: replace-cross Abstract: The rapid advancement of large language models (LLMs) has enabled new possibilities for applying artificial intelligence within the legal doma

Watching Movies Like a Human: Egocentric Emotion Understanding for Embodied Companions

arXiv:2604.15823v1 Announce Type: new Abstract: Embodied robotic agents often perceive movies through an egocentric screen-view interface rather than native cinematic footage, introducing domain shift

When Cultures Meet: Multicultural Text-to-Image Generation

arXiv:2502.15972v2 Announce Type: replace-cross Abstract: Text-to-image generation models have achieved strong performance in culturally homogeneous settings, yet their ability to generate multicultur

When Surfaces Lie: Exploiting Wrinkle-Induced Attention Shift to Attack Vision-Language Models

arXiv:2603.27759v3 Announce Type: replace Abstract: Visual-Language Models (VLMs) have demonstrated exceptional cross-modal understanding across various tasks, including zero-shot classification, imag

Why Fine-Tuning Encourages Hallucinations and How to Fix It

arXiv:2604.15574v1 Announce Type: cross Abstract: Large language models are prone to hallucinating factually incorrect statements. A key source of these errors is exposure to new factual information t

Wisdom is Knowing What not to Say: Hallucination-Free LLMs Unlearning via Attention Shifting

arXiv:2510.17210v3 Announce Type: replace Abstract: The increase in computing power and the necessity of AI-assisted decision-making boost the growing application of large language models (LLMs). Alon

3D Instruction Ambiguity Detection

arXiv:2601.05991v2 Announce Type: replace Abstract: In safety-critical domains, linguistic ambiguity can have severe consequences; a vague command like 'Pass me the vial' in a surgical setting could l

A multi-platform LiDAR dataset for standardized forest inventory measurement at long term ecological monitoring sites

model-releasesarxiv-cs-ro

arXiv:2604.14635v1 Announce Type: new Abstract: We present a curated multi-platform LiDAR reference dataset from an instrumented ICOS forest plot, explicitly designed to support calibration, benchmark

A Nonlinear Separation Principle: Applications to Neural Networks, Control and Learning

arXiv:2604.15238v1 Announce Type: cross Abstract: This paper investigates continuous-time and discrete-time firing-rate and Hopfield recurrent neural networks (RNNs), with applications in nonlinear co

AccelOpt: A Self-Improving LLM Agentic System for AI Accelerator Kernel Optimization

arXiv:2511.15915v2 Announce Type: replace-cross Abstract: We present AccelOpt, a self-improving large language model (LLM) agentic system that autonomously optimizes kernels for emerging AI acclerator

Acceptance Dynamics Across Cognitive Domains in Speculative Decoding

arXiv:2604.14682v1 Announce Type: cross Abstract: Speculative decoding accelerates large language model (LLM) inference. It uses a small draft model to propose a tree of future tokens. A larger target

Active Learning with Selective Time-Step Acquisition for PDEs

arXiv:2511.18107v2 Announce Type: replace Abstract: Accurately solving partial differential equations (PDEs) is critical to understanding complex scientific and engineering phenomena, yet traditional

AD4AD: Benchmarking Visual Anomaly Detection Models for Safer Autonomous Driving

arXiv:2604.15291v1 Announce Type: new Abstract: The reliability of a machine vision system for autonomous driving depends heavily on its training data distribution. When a vehicle encounters significa

ADAPT: Benchmarking Commonsense Planning under Unspecified Affordance Constraints

arXiv:2604.14902v1 Announce Type: cross Abstract: Intelligent embodied agents should not simply follow instructions, as real-world environments often involve unexpected conditions and exceptions. Howe

Adaptive Test-Time Compute Allocation for Reasoning LLMs via Constrained Policy Optimization

arXiv:2604.14853v1 Announce Type: new Abstract: Test-time compute scaling, the practice of spending extra computation during inference via repeated sampling, search, or extended reasoning, has become

AgentGA: Evolving Code Solutions in Agent-Seed Space

arXiv:2604.14655v1 Announce Type: cross Abstract: We present AgentGA, a framework that evolves autonomous code-generation runs by optimizing the agent seed: the task prompt plus optional parent archiv

AgentIAD: Agentic Industrial Anomaly Detection via Adaptive Memory Augmentation

arXiv:2512.13671v2 Announce Type: replace Abstract: Industrial anomaly detection (IAD) is challenging due to the subtle and highly localized nature of many defects, which single-pass vision--language

AI-Assisted Peer Review at Scale: The AAAI-26 AI Review Pilot

arXiv:2604.13940v1 Announce Type: new Abstract: Scientific peer review faces mounting strain as submission volumes surge, making it increasingly difficult to sustain review quality, consistency, and t

AnimationBench: Are Video Models Good at Character-Centric Animation?

arXiv:2604.15299v1 Announce Type: new Abstract: Video generation has advanced rapidly, with recent methods producing increasingly convincing animated results. However, existing benchmarks-largely desi

Anonpsy: A Graph-Based Framework for Structure-Preserving De-identification of Psychiatric Narratives

arXiv:2601.13503v2 Announce Type: replace Abstract: Psychiatric narratives encode patient identity not only through explicit identifiers but also through idiosyncratic life events embedded in their cl

Applying an Agentic Coding Tool for Improving Published Algorithm Implementations

arXiv:2604.13109v1 Announce Type: cross Abstract: We present a two-stage pipeline for AI-assisted improvement of published algorithm implementations. In the first stage, a large language model with re

Assessment Design in the AI Era: A Method for Identifying Items Functioning Differentially for Humans and Chatbots

arXiv:2603.23682v2 Announce Type: replace-cross Abstract: The rapid adoption of large language models (LLMs) in education raises profound challenges for assessment design. To adapt assessments to the

AutoRAN: Automated Hijacking of Safety Reasoning in Large Reasoning Models

arXiv:2505.10846v3 Announce Type: replace Abstract: This paper presents AutoRAN, the first framework to automate the hijacking of internal safety reasoning in large reasoning models (LRMs). At its cor

Auxiliary Finite-Difference Residual-Gradient Regularization for PINNs

arXiv:2604.14472v1 Announce Type: new Abstract: Physics-informed neural networks (PINNs) are often selected by a single scalar loss even when the quantity of interest is more specific. We study a hybr

Benchmarking Classical Coverage Path Planning Heuristics on Irregular Hexagonal Grids for Maritime Coverage Scenarios

model-releasesarxiv-cs-ro

arXiv:2604.15202v1 Announce Type: new Abstract: Coverage path planning on irregular hexagonal grids is relevant to maritime surveillance, search and rescue and environmental monitoring, yet classical

Benchmarking Linguistic Adaptation in Comparable-Sized LLMs: A Study of Llama-3.1-8B, Mistral-7B-v0.1, and Qwen3-8B on Romanized Nepali

arXiv:2604.14171v1 Announce Type: new Abstract: Romanized Nepali, the Nepali language written in the Latin alphabet, is the dominant medium for informal digital communication in Nepal, yet it remains

Benchmarking Optimizers for MLPs in Tabular Deep Learning

arXiv:2604.15297v1 Announce Type: new Abstract: MLP is a heavily used backbone in modern deep learning (DL) architectures for supervised learning on tabular data, and AdamW is the go-to optimizer used

Best of both worlds: Stochastic & adversarial best-arm identification

arXiv:2604.14860v1 Announce Type: cross Abstract: We study bandit best-arm identification with arbitrary and potentially adversarial rewards. A simple random uniform learner obtains the optimal rate o

BiCon-Gate: Consistency-Gated De-colloquialisation for Dialogue Fact-Checking

arXiv:2604.14389v1 Announce Type: new Abstract: Automated fact-checking in dialogue involves multi-turn conversations where colloquial language is frequent yet understudied. To address this gap, we pr

Bridging the Gap between Learning and Inference for Diffusion-Based Molecule Generation

arXiv:2411.05472v2 Announce Type: replace Abstract: The paradigm shift toward structure-driven molecule generation has been propelled by advances in deep generative models, such as variational auto-en

Building Extraction from Remote Sensing Imagery under Hazy and Low-light Conditions: Benchmark and Baseline

arXiv:2604.15088v1 Announce Type: new Abstract: Building extraction from optical Remote Sensing (RS) imagery suffers from performance degradation under real-world hazy and low-light conditions. Howeve

CaptionQA: Is Your Caption as Useful as the Image Itself?

arXiv:2511.21025v2 Announce Type: replace Abstract: Image captions serve as efficient surrogates for visual content in multimodal systems such as retrieval, recommendation, and multi-step agentic infe

Catching Every Ripple: Enhanced Anomaly Awareness via Dynamic Concept Adaptation

arXiv:2604.14726v1 Announce Type: new Abstract: Online anomaly detection (OAD) plays a pivotal role in real-time analytics and decision-making for evolving data streams. However, existing methods ofte

CausalDetox: Causal Head Selection and Intervention for Language Model Detoxification

arXiv:2604.14602v1 Announce Type: new Abstract: Large language models (LLMs) frequently generate toxic content, posing significant risks for safe deployment. Current mitigation strategies often degrad

CAVERS: Multimodal SLAM Data from a Natural Karstic Cave with Ground Truth Motion Capture

model-releasesarxiv-cs-ro

arXiv:2604.15052v1 Announce Type: new Abstract: Autonomous robots operating in natural karstic caves face perception and navigation challenges that are qualitatively distinct from those encountered in

ChatSVA: Bridging SVA Generation for Hardware Verification via Task-Specific LLMs

arXiv:2604.02811v2 Announce Type: replace-cross Abstract: Functional verification consumes over 50% of the IC development lifecycle, where SystemVerilog Assertions (SVAs) are indispensable for formal

Chinese Language Is Not More Efficient Than English in Vibe Coding: A Preliminary Study on Token Cost and Problem-Solving Rate

arXiv:2604.14210v1 Announce Type: new Abstract: A claim has been circulating on social media and practitioner forums that Chinese prompts are more token-efficient than English for LLM coding tasks, po

Class Unlearning via Depth-Aware Removal of Forget-Specific Directions

arXiv:2604.15166v1 Announce Type: new Abstract: Machine unlearning aims to remove targeted knowledge from a trained model without the cost of retraining from scratch. In class unlearning, however, red

CLion: Efficient Cautious Lion Optimizer with Enhanced Generalization

arXiv:2604.14587v1 Announce Type: new Abstract: Lion optimizer is a popular learning-based optimization algorithm in machine learning, which shows impressive performance in training many deep learning

CobwebTM: Probabilistic Concept Formation for Lifelong and Hierarchical Topic Modeling

arXiv:2604.14489v1 Announce Type: new Abstract: Topic modeling seeks to uncover latent semantic structure in text corpora with minimal supervision. Neural approaches achieve strong performance but req

Comparison of Modern Multilingual Text Embedding Techniques for Hate Speech Detection Task

arXiv:2604.14907v1 Announce Type: new Abstract: Online hate speech and abusive language pose a growing challenge for content moderation, especially in multilingual settings and for low-resource langua

Compressed-Sensing-Guided, Inference-Aware Structured Reduction for Large Language Models

arXiv:2604.14156v1 Announce Type: new Abstract: Large language models deliver strong generative performance but at the cost of massive parameter counts, memory use, and decoding latency. Prior work ha

Constrained Decoding for Safe Robot Navigation Foundation Models

arXiv:2509.01728v4 Announce Type: replace-cross Abstract: Recent advances in the development of robotic foundation models have led to promising end-to-end and general-purpose capabilities in robotic s

Contract-Coding: Towards Repo-Level Generation via Structured Symbolic Paradigm

arXiv:2604.13100v1 Announce Type: cross Abstract: The shift toward intent-driven software engineering (often termed 'Vibe Coding') exposes a critical Context-Fidelity Trade-off: vague user intents ove

ContractSkill: Repairable Contract-Based Skills for Multimodal Web Agents

arXiv:2603.20340v3 Announce Type: replace-cross Abstract: Self-generated skills for web agents are often unstable and can even hurt performance relative to direct acting. We argue that the key bottlen