Search: “model-releases”

A Co-Design Framework for High-Performance Jumping of a Five-Bar Monoped with Actuator Optimization

model-releasesarxiv-cs-ro

arXiv:2604.06025v2 Announce Type: replace Abstract: The performance of legged robots depends strongly on both mechanical design and control, motivating co-design approaches that jointly optimize these

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Model Releases

A Failure-Mode Benchmark for Polymorphic Sybil Poisoning in RAG

DGX agent

arXiv:2607.03739v1 Announce Type: cross Abstract: We release a benchmark and failure-mode-aware evaluation framework for grounded QA under coordinated retrieval poisoning. The framework partitions rea

model-releasesarxiv-cs-ai

7 Jul 2026

A Fair Benchmarking of Deep Relational Database Learning Models

arXiv:2607.03659v1 Announce Type: cross Abstract: Relational databases (RDBs) are the primary data infrastructure in many enterprises, yet recent deep learning methods designed for RDBs have been eval

A Gradient Flow Perspective on Minimum MMD Estimation

arXiv:2607.03871v1 Announce Type: new Abstract: Minimum maximum mean discrepancy (MMD) estimation has emerged as a robust and likelihood-free alternative to maximum likelihood estimation for parameter

A Large-Scale Dataset and a New Method for RemoteSensing Traffic Object Segmentation

arXiv:2607.03945v1 Announce Type: new Abstract: Remote sensing imagery plays a crucial role in evaluating regional transportation capacity. However, existing segmentation datasets often lack diversity

A Near-Linear-Time Solver for Graph p-Laplacian Semi-Supervised Learning via Continuation in p

arXiv:2607.03503v1 Announce Type: new Abstract: Graph-based semi-supervised learning (SSL) propagates a few labels over a similarity graph by minimizing a Dirichlet-type energy. The standard quadratic

A Reliable Context-Aware and Temporal Planning Framework for Autonomous Driving

arXiv:2607.04689v1 Announce Type: cross Abstract: Safe operation of autonomous vehicles in dense urban traffic depends on perception and planning that remain reliable when onboard sensing is degraded.

A Retrieval-Augmented Framework for Detecting and Resolving Pragmatic Ambiguities in Natural Language Requirements

arXiv:2607.04436v1 Announce Type: cross Abstract: Natural language requirements (NLRs) are essential for bridging communication gaps among diverse stakeholders in software development. However, the in

A Step Towards Robust Unsupervised Domain Adaptation via Fine-Tuning and Reinforcement Learning

arXiv:2607.03600v1 Announce Type: cross Abstract: Adversarial robustness in Unsupervised Domain Adaptation (UDA) remains a significant challenge due to noisy pseudo labels and inherent distributional

A Structural Interpretation of GELU and Threshold-Transmission Activations via the First-Order Loss Function

arXiv:2607.03664v1 Announce Type: new Abstract: The Gaussian Error Linear Unit is usually motivated as the expected output of an input-dependent stochastic Bernoulli gate. This work gives a complement

A Systematic Survey on Large Language Models for Evolutionary Optimization: From Modeling to Solving

arXiv:2509.08269v5 Announce Type: replace-cross Abstract: Large language models (LLMs) are increasingly integrated with evolutionary computation to support optimization tasks. This survey primarily fo

A Technical Survey of Reinforcement Learning Techniques for Large Language Models

arXiv:2507.04136v2 Announce Type: replace Abstract: This survey offers a comprehensive foundation on the integration of RL with language models, highlighting prominent algorithms such as Proximal Poli

Adversarial LassoNet: Robust Feature Selection via Stability-Driven Sparse Learning

arXiv:2607.03839v1 Announce Type: new Abstract: Sparse feature selection is critical for high-dimensional machine learning, yet traditional ell_1-regularized methods are often brittle under observatio

Agent Data Injection Attacks are Realistic Threats to AI Agents

arXiv:2607.05120v1 Announce Type: cross Abstract: AI agents act on behalf of user prompts, consuming external data and taking actions based on the agent context. Prior research on AI agent security ha

Agent-driven Long-tail Simulation for Autonomous Driving

arXiv:2607.04331v1 Announce Type: cross Abstract: Evaluating autonomous driving systems in closed-loop settings requires realistic and interactive simulation, yet existing simulators largely rely on l

Agent Step Value: State-Transition Measurement with State-Grounded LLM Evaluators

arXiv:2607.04419v1 Announce Type: new Abstract: Most agent evaluations collapse a multi-step trace into a final answer, a success flag, or a trajectory-level score. These aggregates obscure the diagno

AgentGym2: Benchmarking Large Language Model Agents in De-Idealized Real-World Environments

arXiv:2607.05174v1 Announce Type: new Abstract: Language agents, i.e., LLM agents, progress rapidly and are increasingly deployed in production environments. This trend underscores the urgent need for

Agentic Retrieval-Augmented Generation for Financial Document Question Answering

arXiv:2605.05409v2 Announce Type: replace Abstract: Financial document question answering (QA) demands complex multi-step numerical reasoning over heterogeneous evidence--structured tables, textual na

AgenticPD: A Stage-Aware Agentic Framework for Physical Design QoR Optimization

arXiv:2607.04758v1 Announce Type: new Abstract: Physical design quality-of-results~(QoR) optimization is hard and expensive. Choices made at one stage can help or hurt later stages. Each evaluation re

AgentLTL: A Trace-Verification Framework for Measuring, Enforcing, and Training Procedural Compliance in Tool-Using LLM Agents

arXiv:2607.02599v1 Announce Type: cross Abstract: Tool-using LLM agents are usually evaluated by final-answer correctness or LLM judges. Neither captures how an answer was produced. In safety-critical

AI Wizards at EXIST 2026: Hierarchical Soft-Label Learning for Multimodal Sexism Identification in Memes

model-releasesarxiv-cs-cl

arXiv:2607.04410v1 Announce Type: new Abstract: We present the AI Wizards submission to EXIST 2026 for multimodal sexism identification in memes. The task is composed of three, increasingly harder sub

Amortising Bayesian Experimental Design for Sequential Information Gathering in LLMs

arXiv:2607.03426v1 Announce Type: cross Abstract: Large language models (LLMs) exhibit strong reasoning and world-knowledge capabilities, yet often struggle to gather information effectively across th

An AI-Assisted Solution to the Signed BAR Conjecture: Uniqueness in the Harrison--Reiman Class and a Completely-S Class Obstruction

arXiv:2607.03639v1 Announce Type: cross Abstract: For a multidimensional reflected diffusion, determining whether the associated basic adjoint relationship (BAR) uniquely characterizes the stationary

Anchored Self-Play for Code Repair

model-releasesarxiv-cs-cl

arXiv:2607.03523v1 Announce Type: cross Abstract: Code repair is an important capability for language models (LMs): given a buggy program and unit tests, an LM must produce a fixed program that passes

AnchorSplat: Fast and Structure Consistent Detail Synthesis for Gaussian Splatting

arXiv:2607.01290v2 Announce Type: replace Abstract: 3D Gaussian Splatting (3DGS) has emerged as a powerful representation for high-fidelity rendering. However, existing assets often suffer from qualit

AnchorVLA: Bridging Discrete Decisions and Continuous Trajectories for Vision-Language-Action Planning

arXiv:2607.03182v1 Announce Type: cross Abstract: Autonomous driving planning requires translating navigation intent, traffic rules, dynamic interactions, and language instructions into executable con

APeB: Benchmarking Personalization Ability of Large Language Model Agents

arXiv:2607.03162v1 Announce Type: new Abstract: LLM-powered agents struggle with personalization when users issue raw, underspecified queries. In this setting, agents must infer latent intent, extract

APEX: Approximate-but-exhaustive search for ultra-large combinatorial synthesis libraries

arXiv:2510.24380v2 Announce Type: replace Abstract: Make-on-demand combinatorial synthesis libraries (CSLs) like Enamine REAL have significantly enabled drug discovery efforts. However, their large si

ARCQuant: Boosting NVFP4 Quantization with Augmented Residual Channels for LLMs

arXiv:2601.07475v2 Announce Type: replace-cross Abstract: The emergence of fine-grained numerical formats like NVFP4 presents new opportunities for efficient Large Language Model (LLM) inference. Howe

Asymptotic-Preserving A Posteriori Analysis of Diffusion and Flow-Matching Samplers

arXiv:2607.04113v1 Announce Type: new Abstract: Diffusion and flow-matching samplers integrate a learned probability-flow ODE from a large noise scale down to a small terminal floor sigma_{min}, at wh

Attention Dynamics in Diffusion Models: A Visual Analytics Framework for Human-AI Collaboration

arXiv:2607.02563v1 Announce Type: cross Abstract: Diffusion-based text-to-image models can synthesize complex and highly structured visual content, yet the emergence and evolution of semantic structur

Attention is Just Another Name for Coupling? A Fast-Slow ODE Perspective on Hierarchical Pretraining

arXiv:2606.16730v2 Announce Type: replace-cross Abstract: We re-interpret Transformer pretraining as a fast-slow, singularly perturbed flow along depth, with untied weights as its non-autonomous featu

AudioX-Turbo: A Unified Framework for Efficient Anything-to-Audio Generation

arXiv:2606.12555v2 Announce Type: replace-cross Abstract: Audio and music generation based on flexible multimodal control signals is a widely applicable topic, with the following key challenges: 1) a

Auditing the Audit: Five Failure Modes in Benchmark-Validity Audits

arXiv:2607.02586v1 Announce Type: new Abstract: Governance frameworks ask AI providers and auditors for documented evaluation evidence, and perturbation-based construct-validity audits are a common fo

Auto-AEG: Scalable Data Construction for Open-Vocabulary Audio Event Grounding

arXiv:2607.04383v1 Announce Type: cross Abstract: Large Audio-Language Models (LALMs) reason fluently about sound yet struggle to localize precisely when events occur, while classical Sound Event Dete

Auto: The AGI Compiler

arXiv:2607.04542v1 Announce Type: cross Abstract: Every LLM agent run re-derives its behavior token by token on a frontier model: brilliant, expensive, slow, and unbounded. We present Auto, a compiler

AutoCedar: An Agentic Framework for Verifier-Guided Access Control Policy Synthesis

arXiv:2607.03656v1 Announce Type: cross Abstract: Large Language Models are increasingly used to turn natural-language requirements into code. In access control, that shortcut is dangerous: a generate

AutoResearch: An Execution-Grounded Multi-Agent Framework for Reliable Research Workflow Automation

arXiv:2607.02520v1 Announce Type: cross Abstract: Automated research agents increasingly generate code, retrieve literature, and draft scientific artifacts, but they often fail to verify whether gener

Back to Basics: Improving Molecular Understanding in LLMs via SMILES-Graph Translation

arXiv:2607.03007v1 Announce Type: cross Abstract: Recent advances in molecular large language models have led to strong performance on molecular understanding and generation tasks, yet these gains oft

BanglaMemeEvidence: A Multimodal Benchmark Dataset for Explanatory Evidence Detection in Bengali Memes

arXiv:2607.03981v1 Announce Type: cross Abstract: Memes have become influential communication tools on social media, combining viral visuals with concise messaging to convey impactful ideas. While sub

Benchmarking API Drift in LLM-Generated Quantum Code Across Successive SDK Versions

arXiv:2607.04072v1 Announce Type: cross Abstract: Large language models can generate plausible quantum code, but it is unclear whether they can reliably target the specific software development kit (S

Beyond Forecasting: The Belief-to-Trade Layer in Prediction-Market Agents

arXiv:2607.03015v1 Announce Type: new Abstract: Forecasting future events has attracted growing attention as a testbed for general-purpose AI. A natural way to ground this evaluation is let the models

Beyond Modality Fusion: Deep Ensembles for Multimodal Classification

arXiv:2607.05019v1 Announce Type: cross Abstract: In multimodal classification, late-fusion approaches classify concatenated modality-specific features extracted by unimodal neural networks. When moda

Beyond Multilingual Averages: MTEB-PT, a Benchmark for Portuguese Sentence Encoders

arXiv:2607.04071v1 Announce Type: cross Abstract: Portuguese remains underrepresented in text embedding evaluation, despite being one of the most widely spoken languages in the world. As a result, emb

Beyond Scene Priors: Fine-Grained Traffic Scene Reasoning with Benchmarking and Query-Guided Small-Object Focus

arXiv:2607.04149v1 Announce Type: new Abstract: In safety-critical traffic scenarios, answering complex questions relies on minute, localized visual cues. However, standard Multimodal Large Language M

Beyond Task Completion: A Verification-vs.-Conformance Gap in Tool-Evolving Agents

arXiv:2604.00392v2 Announce Type: replace-cross Abstract: Agents that synthesize their own tools ship a second artifact alongside each answer: a software library that future tasks reuse, compose, and

Boundary-layer asymptotics for Gaussian-smoothed singular measures

arXiv:2607.04514v1 Announce Type: cross Abstract: We study the small-noise asymptotics of Euclidean heat regularizations of probability measures supported on manifolds with corners. Near a boundary or

Brand-as-Memory: Vision-Language Models Encode Causal, Mechanistically Localizable Credibility Priors for News Sources

arXiv:2607.03365v1 Announce Type: cross Abstract: Vision-language models (VLMs) increasingly read news and web content as images, where the publisher's identity is visually present. We show that VLMs