Search: “model-releases”

Multi-Agent Forensic Reasoning for Generalizable Deepfake Video Detection

arXiv:2608.06865v1 Announce Type: cross Abstract: The malicious use of generative artificial intelligence to create highly realistic deepfake videos raises serious ethical concerns and poses substanti

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Model Releases

Multi Codec Discrete Diffusion Model for Text Guided Speech Inpainting and Editing

DGX agent

arXiv:2608.06424v1 Announce Type: cross Abstract: Speech recordings often contain missing, corrupted, or incorrect regions that must be reconstructed or modified without re-synthesizing the entire utt

model-releasesarxiv-cs-cl

10 Aug 2026

Multi-Level Modeling of Large Language Model Inference Latency and Energy via Hybrid Analytical--Machine-Learning Predictors

arXiv:2608.06723v1 Announce Type: cross Abstract: The rapid scaling of Large Language Models (LLMs) has significantly increased computational cost, energy consumption, and inference latency, making ac

Multiple Hypothesis Flow Estimation for Video Frame Interpolation under Matching Ambiguity

arXiv:2608.07120v1 Announce Type: new Abstract: Many flow-based video frame interpolation (VFI) methods synthesize an intermediate frame by estimating optical flow fields, warping the two input frames

Multiscale Reward Hedging from Correct Demonstrations

arXiv:2608.06825v1 Announce Type: new Abstract: Learning from correct demonstrations is harder than supervised learning when many answers are correct: after predicting, the learner sees one valid answ

MultiView-Bench: A Diagnostic Benchmark for World-Centric Multi-View Integration in VLMs

arXiv:2607.08970v2 Announce Type: replace-cross Abstract: Recent benchmarks for VLMs largely assess single- or limited-view perception, leaving untested the core cognitive ability to integrate observa

Newton-Schulz Retraction-Based Inference Enables Hidden Quantum Markov Models to Outperform Classical HMMs

arXiv:2608.06554v1 Announce Type: new Abstract: Hidden Markov models (HMMs) are widely used probabilistic models for discrete sequential data but can be limited when hidden dynamics are complex. Hidde

NiyamAI - An Intent-Bound AI Agent with Cryptographically Verifiable Guardrails using Zero-Knowledge Proofs

arXiv:2608.07167v1 Announce Type: new Abstract: Giving an AI agent the ability to send emails, query databases, or execute commands is useful--until the agent is tricked into doing something it should

Not All Problems Are Best Modeled as MILP: A DSL-Centric Framework for Flexible and Accurate Optimization Modeling

arXiv:2608.07040v1 Announce Type: new Abstract: Solving combinatorial optimization problems (COPs) requires not only efficient algorithms but also carefully crafted formulations. While recent works ha

Optimal Neural Network Approximation via Empirical Least Squares with Deterministic Samples

arXiv:2608.06687v1 Announce Type: cross Abstract: We develop a rigorous theory of discrete residual least-squares approximation for elliptic spectral equations mathfrak L_eta u=f using linearized ReLU

Panoramic Multimodal Semantic Occupancy Prediction for Quadruped Robots

arXiv:2603.13108v2 Announce Type: replace-cross Abstract: Panoramic imagery provides holistic 360{eg} visual coverage for environmental perception in quadruped robots. However, existing occupancy pred

PHASE-Tree: Modeling Character-State Evolution in Long-Horizon Role-Playing Dialogue

arXiv:2608.06975v1 Announce Type: cross Abstract: Long-horizon role-playing demands that characters remain recognizable as they evolve with the narrative. Yet existing work falls short on two fronts:

PHOENIX: Fine-Tuned SLM-Powered Autonomous Satellite Lifetime Extension via Predictive Self-Healing and Multi-Agent AI Recovery

arXiv:2608.07126v1 Announce Type: cross Abstract: Most CubeSats, small and low-cost satellites roughly the size of a shoebox, do not survive as long as they were designed to: a study of 178 missions f

Policy-Masked Private Experts: Auditable and Reversible Capability Access Control in Sparse MoE Models

arXiv:2608.06690v1 Announce Type: cross Abstract: Most language-model access controls regulate behavior while leaving the same computation available to every request. We study a different systems ques

Post-Grokking Collapse at the Representation-Readout Interface in Muon-Trained Transformers

arXiv:2608.07436v1 Announce Type: new Abstract: Under the standard split, Muon gets hidden matrices and AdamW embeddings/output head. Muon groks modular addition faster, but its solutions do not hold.

PURe: A Plug-and-Play Product-Unit Residual Module for Vision Networks

arXiv:2505.04397v3 Announce Type: replace-cross Abstract: Modern vision networks are dominated by additive local transformations, whereas explicit multiplicative local interactions remain underexplore

Quantization Damage Is Multiplicative, Not Additive

arXiv:2608.06564v1 Announce Type: cross Abstract: Quantization is how large language models are actually deployed, and below four bits it is known to hurt. What nobody can say is which of the model's

RegionDet: A Benchmark for Region Detection Beyond Object Instances

arXiv:2608.06850v1 Announce Type: new Abstract: Object detection is a fundamental task in computer vision and has achieved remarkable progress on standard benchmarks by localizing discrete and well-bo

ResidencyRL: Reinforcement Learning in Simulated Clinical Environments

arXiv:2608.07418v1 Announce Type: new Abstract: In medical education, physicians convert academic knowledge into clinical expertise through residency: years of training across thousands of encounters,

Retrieval-Constrained Policy Optimization for Attack Technique Extraction from Cyber Threat Intelligence

arXiv:2608.06778v1 Announce Type: cross Abstract: Mapping cyber threat intelligence (CTI) text to MITRE ATT&CK techniques is essential for structured threat analysis, yet manual annotation is costly a

Retrofitting Linear Attention into Diffusion Language Models

arXiv:2608.06628v1 Announce Type: new Abstract: Diffusion language models (dLLMs) offer a promising alternative to autoregressive models by accelerating inference through parallel decoding. Recent dLL

RoRA: Role-Oriented Regional Allocation for Visual Token Pruning in MLLMs

arXiv:2608.07088v1 Announce Type: cross Abstract: Multimodal large language models (MLLMs) encode images as long visual token sequences, making prefilling and KV-cache storage expensive. Existing trai

SABRE: Scalable and Automated Benchmarking of VLMs under Stress

arXiv:2608.07435v1 Announce Type: cross Abstract: Vision-language models (VLMs) are improving rapidly, but benchmark development lags behind, making weaknesses hard to identify. Building stress tests

SAGEO Arena: A Realistic Environment for Evaluating Search-Augmented Generative Engine Optimization

arXiv:2602.12187v2 Announce Type: replace-cross Abstract: Search-Augmented Generative Engines (SAGE) have emerged as a new paradigm for information access, bridging web-scale retrieval with generative

Same physical state, different collective dynamics: state encodings select synchronization outcomes in language-model agents

arXiv:2608.06968v1 Announce Type: cross Abstract: Language-model agents act on state encodings of their environment, yet these are treated as interchangeable interfaces. Using pretrained language mode

Science Edge Evaluation: SEE the Missing Step Toward Real Scientific Discovery

arXiv:2608.06931v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly involved in scientific discovery, yet it remains unclear whether they can support complex real laboratory

Seeking SOTA: Time-Series Forecasting Must Adopt Taxonomy-Specific Evaluation to Dispel Illusory Gains

arXiv:2603.15506v2 Announce Type: replace-cross Abstract: We argue that the current practice of evaluating AI/ML time-series forecasting models, predominantly on benchmarks characterized by strong, pe

Semantic Adapter Routing with Fine-Tuning Task Embeddings

arXiv:2606.19079v2 Announce Type: replace Abstract: Parameter-efficient fine-tuning (PEFT) has led to model ecosystems in which a single backbone is paired with many task-specialized adapters. Given s

Simple-OPD: Demystifying Warm-up for On-policy Distillation

arXiv:2608.06802v1 Announce Type: new Abstract: On-policy distillation (OPD) trains a student on its own rollouts with token-level supervision from teacher models, but its effectiveness can depend str

SkySeaLand: A Wide-Format Satellite Transportation Benchmark with an Ultra-Lightweight Detection Baseline

arXiv:2608.07382v1 Announce Type: new Abstract: Satellite object detection is challenged by small targets and wide-format scenes that lose detail under standard square-input resizing. We introduce Sky

SLED: Scalable Location Encoding via Distillation

arXiv:2608.06612v1 Announce Type: cross Abstract: The plethora of readily available geospatial data offers exciting opportunities to learn high quality representations of the planet, but the sheer siz

Social World Models

arXiv:2509.00559v3 Announce Type: replace Abstract: Humans intuitively navigate social interactions by simulating unspoken dynamics and reasoning about others' perspectives, even with limited informat

SparseVoxelDet: Fully Sparse Voxel Networks for Efficient Event-Based Drone Detection

arXiv:2603.21638v2 Announce Type: replace Abstract: Event cameras excel at detecting small, fast drones, but today's detectors give away their key advantage: they convert the sparse event stream into

Spatiotemporal Agility: Time-Constrained Reinforcement Learning for Vision-Guided Dynamic Quadrupedal Interception

model-releasesarxiv-cs-ro

arXiv:2608.06907v1 Announce Type: new Abstract: Legged robots require robust agility to perceive and interact with complex and dynamic environments within a constrained time. However, most existing qu

Stable Curves, Unstable Items: Item-Level Scaling Heterogeneity in Video LLMs

arXiv:2608.07014v1 Announce Type: new Abstract: Aggregate scaling curves suggest that Video LLMs improve smoothly or saturate as visual budgets grow. We show that this view can conceal large, opposing

StepJack: Benchmarking Computer-Use Agent Safety Against Multi-Step Indirect Prompt Injection

arXiv:2608.06477v1 Announce Type: cross Abstract: Computer-use agents (CUAs) face a growing threat from indirect prompt injection, where adversarial instructions are planted in the environment such as

Stockmark-Nemotron-3-Nano-Omni-JapanDocReader: Structured Document Parsing via Capability Injection and Forgetting Control

arXiv:2608.06758v1 Announce Type: new Abstract: We present Stockmark-Nemotron-3-Nano-Omni-JapanDocReader, a Japanese document understanding model built from Nemotron-3-Nano-Omni-30B-A3B-Reasoning-BF16

Stoicheia: Character-Level Masked Diffusion for Ancient Greek Textual Restoration, Parsing, and Metrical Scansion

arXiv:2608.07249v1 Announce Type: new Abstract: We introduce Stoicheia, a 405M-parameter character-level masked-diffusion encoder for Ancient Greek whose input factors into five aligned, independently

Sub-Quadratic Bisimulation Metrics via Approximate Nearest Neighbors: Coverage-Augmented Guarantees and Computable Two-Sided Certificates

arXiv:2608.06762v1 Announce Type: new Abstract: Bisimulation metrics quantify behavioral similarity in Markov decision processes, but their Wasserstein fixed-point operator updates every state pair an

Suppress and Diversify: Refining Robust Pathways for Corruption Robustness

arXiv:2608.06712v1 Announce Type: new Abstract: Model robustness against natural image corruptions is essential for safety-critical applications. While existing methods primarily focus on implicit rep

Surg-UniWorld: A Unified Surgical World Model with Multimodal Control Experts

arXiv:2608.06770v1 Announce Type: new Abstract: Controllable surgical world models can provide a generative foundation for surgical artificial intelligence and simulation by synthesizing realistic ins

Symbolic Graphics Programming with Large Language Models

arXiv:2509.05208v2 Announce Type: replace Abstract: Large language models (LLMs) excel at program synthesis, yet their ability to produce symbolic graphics programs (SGPs) that render into precise vis

TEMPO: Semantic-Action Decoupled RL Post-Training for Vision-Language-Action Models

arXiv:2608.07314v1 Announce Type: cross Abstract: Vision-language-action (VLA) models are commonly adapted to downstream manipulation tasks via supervised fine-tuning (SFT) or online reinforcement lea

Tensor Network Kernel Machines: A JAX Framework for Machine Learning and Nonlinear System Identification

arXiv:2608.07043v1 Announce Type: cross Abstract: Developing nonlinear models that are both expressive and computationally efficient remains a challenge in machine learning and nonlinear system identi

Test-Time Adaptation with Online Personalized Energy-Based Cache for Fine-Grained Video Expression Recognition

arXiv:2608.06467v1 Announce Type: new Abstract: Facial expression recognition (FER) in videos is challenging because models must identify subtle, temporally evolving affective states that vary across

The Sparsity Whisperer

arXiv:2608.06630v1 Announce Type: new Abstract: Pruning reduces the inference cost of large language models, but existing criteria primarily preserve large activations or reconstruct layer outputs. We

TRACE: A Multi-Layer Benchmark for Human AI Controller Coordination Under Drift and Failure

arXiv:2608.06657v1 Announce Type: new Abstract: Modern cyber-physical and AI-assisted systems couple human operators, AI decision modules, and automated controllers in a single control loop, so trustw

TradeVerse: A Longitudinal Benchmark of Political Negotiation in International Trade

arXiv:2608.06549v1 Announce Type: cross Abstract: LLMs are increasingly being applied to tasks involving institutional and political texts, but existing benchmarks evaluate them on isolated documents