Search: “models”

arXiv:2404.14642v4 Announce Type: replace Abstract: Graphical models have demonstrated their exceptional capabilities across numerous applications. However, their performance, confidence, and trustwor

applicationsarxiv-cs-lg

15 Apr 2026

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3D-Anchored Lookahead Planning for Persistent Robotic Scene Memory via World-Model-Based MCTS

DGX agent

arXiv:2604.11302v1 Announce Type: cross Abstract: We present 3D-Anchored Lookahead Planning (3D-ALP), a System 2 reasoning engine for robotic manipulation that combines Monte Carlo Tree Search (MCTS)

researcharxiv-cs-ai

14 Apr 2026

Aligning What LLMs Do and Say: Towards Self-Consistent Explanations

arXiv:2506.07523v3 Announce Type: replace Abstract: Large language models (LLMs) seem to offer an easy path to interpretability: just ask them to explain their answers. Yet the features driving an ans

Local Ai

Beyond Model Design: Data-Centric Training and Self-Ensemble for Gaussian Color Image Denoising

arXiv:2604.11468v1 Announce Type: new Abstract: This paper presents our solution to the NTIRE 2026 Image Denoising Challenge (Gaussian color image denoising at fixed noise level sigma = 50). Rather th

local-aiarxiv-cs-cv

CAGenMol: Condition-Aware Diffusion Language Model for Goal-Directed Molecular Generation

arXiv:2604.11483v1 Announce Type: new Abstract: Goal-directed molecular generation requires satisfying heterogeneous constraints such as protein--ligand compatibility and multi-objective drug-like pro

safetyarxiv-cs-lg

COSMIK-MPPI: Scaling Constrained Model Predictive Control to Collision Avoidance in Close-Proximity Dynamic Human Environments

arXiv:2604.10358v1 Announce Type: new Abstract: Ensuring safe physical interaction between torque-controlled manipulators and humans is essential for deploying robots in everyday environments. Model P

safetyarxiv-cs-ro

Eliciting Medical Reasoning with Knowledge-enhanced Data Synthesis: A Semi-Supervised Reinforcement Learning Approach

arXiv:2604.11547v1 Announce Type: cross Abstract: While large language models hold promise for complex medical applications, their development is hindered by the scarcity of high-quality reasoning dat

Local Ai

Long-Horizon Streaming Video Generation via Hybrid Attention with Decoupled Distillation

arXiv:2604.10103v1 Announce Type: new Abstract: Streaming video generation (SVG) distills a pretrained bidirectional video diffusion model into an autoregressive model equipped with sliding window att

local-aiarxiv-cs-cv

Agents

Machine Learning-Based Detection of MCP Attacks

arXiv:2604.10534v1 Announce Type: cross Abstract: The Model Context Protocol (MCP) is a new and emerging technology that extends the functionality of large language models, improving workflows but als

agentsarxiv-cs-ai

Prompt Injection as Role Confusion

arXiv:2603.12277v3 Announce Type: replace-cross Abstract: Language models remain vulnerable to prompt injection attacks despite extensive safety training. We trace this failure to role confusion: mode

safetyarxiv-cs-ai

SHARE: Social-Humanities AI for Research and Education

arXiv:2604.11152v1 Announce Type: new Abstract: This intermediate technical report introduces the SHARE family of base models and the MIRROR user interface. The SHARE models are the first causal langu

The Salami Slicing Threat: Exploiting Cumulative Risks in LLM Systems

arXiv:2604.11309v1 Announce Type: cross Abstract: Large Language Models (LLMs) face prominent security risks from jailbreaking, a practice that manipulates models to bypass built-in security constrain

Training-Free Model Ensemble for Single-Image Super-Resolution via Strong-Branch Compensation

arXiv:2604.11564v1 Announce Type: new Abstract: Single-image super-resolution has progressed from deep convolutional baselines to stronger Transformer and state-space architectures, yet the correspond

researcharxiv-cs-cv

Tutorials

Transformers Learn the Optimal DDPM Denoiser for Multi-Token GMMs

arXiv:2604.10074v1 Announce Type: new Abstract: Transformer-based diffusion models have demonstrated remarkable performance at generating high-quality samples. However, our theoretical understanding o

tutorialsarxiv-cs-lg

VLMaterial: Vision-Language Model-Based Camera-Radar Fusion for Physics-Grounded Material Identification

arXiv:2604.11671v1 Announce Type: cross Abstract: Accurate material recognition is a fundamental capability for intelligent perception systems to interact safely and effectively with the physical worl

safetyarxiv-cs-ro

BEDTime: A Unified Benchmark for Automatically Describing Time Series

arXiv:2509.05215v3 Announce Type: replace Abstract: Recent works propose complex multi-modal models that handle both time series and language, ultimately claiming high performance on complex tasks lik

How Should Video LLMs Output Time? An Analysis of Efficient Temporal Grounding Paradigms

arXiv:2604.08966v1 Announce Type: new Abstract: While Multimodal Large Language Models (MLLMs) have advanced Video Temporal Grounding (VTG), existing methods often couple output paradigms with differe

Agents

Multi-User Large Language Model Agents

arXiv:2604.08567v1 Announce Type: new Abstract: Large language models (LLMs) and LLM-based agents are increasingly deployed as assistants in planning and decision making, yet most existing systems are

agentsarxiv-cs-cl

Task-agnostic Low-rank Residual Adaptation for Efficient Federated Continual Fine-Tuning

arXiv:2505.12318v2 Announce Type: replace Abstract: Federated Parameter-Efficient Fine-Tuning (Fed-PEFT) enables lightweight adaptation of large pre-trained models in federated learning settings by up

The nextAI Solution to the NeurIPS 2023 LLM Efficiency Challenge

arXiv:2604.09034v1 Announce Type: new Abstract: The rapid evolution of Large Language Models (LLMs) has significantly impacted the field of natural language processing, but their growing complexity ra

GameWorld: Towards Standardized and Verifiable Evaluation of Multimodal Game Agents

arXiv:2604.07429v1 Announce Type: new Abstract: Towards an embodied generalist for real-world interaction, Multimodal Large Language Model (MLLM) agents still suffer from challenging latency, sparse f

GEAR: GEometry-motion Alternating Refinement for Articulated Object Modeling with Gaussian Splatting

arXiv:2604.07728v1 Announce Type: new Abstract: High-fidelity interactive digital assets are essential for embodied intelligence and robotic interaction, yet articulated objects remain challenging to

researcharxiv-cs-cv

How Does Machine Learning Manage Complexity?

arXiv:2604.07233v1 Announce Type: new Abstract: We provide a computational complexity lens to understand the power of machine learning models, particularly their ability to model complex systems. Mach

researcharxiv-cs-lg

IatroBench: Pre-Registered Evidence of Iatrogenic Harm from AI Safety Measures

arXiv:2604.07709v1 Announce Type: cross Abstract: Ask a frontier model how to taper six milligrams of alprazolam (psychiatrist retired, ten days of pills left, abrupt cessation causes seizures) and it

Lost in Cultural Translation: Do LLMs Struggle with Math Across Cultural Contexts?

arXiv:2503.18018v2 Announce Type: replace Abstract: We demonstrate that large language models' (LLMs) mathematical reasoning is culturally sensitive: testing 14 models from Anthropic, OpenAI, Google,

MDP modeling for multi-stage stochastic programs

arXiv:2509.22981v2 Announce Type: replace Abstract: We study a class of multi-stage stochastic programs, which incorporate modeling features from Markov decision processes (MDPs). This class includes

safetyarxiv-cs-lg

Tutorials

OceanMAE: A Foundation Model for Ocean Remote Sensing

arXiv:2604.08171v1 Announce Type: new Abstract: Accurate ocean mapping is essential for applications such as bathymetry estimation, seabed characterization, marine litter detection, and ecosystem moni

tutorialsarxiv-cs-cv

AVC-Reward: Event-Centric Audio-Video Consistency Evaluation

arXiv:2610.22321v1 Announce Type: cross Abstract: As joint audio-video generation models become more capable, they can generate audio-visual scenes exhibiting three forms of complexity: multi-event co

CAT-alyzing Honesty: Continuous Adversarial Training for Transferable LLM Honesty

arXiv:2610.22292v1 Announce Type: cross Abstract: Large language models (LLMs) are becoming prevalent in scenarios where honesty is critical. However, despite alignment training, these models still ex

Comfortably Stuck: Evaluation Pitfalls in Bench2Drive's Closed-Loop Protocol

model-releasesarxiv-cs-ro

arXiv:2610.21741v1 Announce Type: new Abstract: Closed-loop evaluation is widely regarded as a more faithful way to assess end-to-end (E2E) driving models than open-loop evaluation, and Bench2Drive, b

Local Ai

Disagreement-Guided Weak-to-Strong Routing

arXiv:2610.22245v1 Announce Type: new Abstract: Small language models are increasingly deployed on edge devices and robotic systems to meet cost and latency constraints, yet their limited capabilities

local-aiarxiv-cs-ai

FlashAttention with Statistics: Low-Overhead Attention Features for Compact Hallucination Detectors

arXiv:2610.21483v1 Announce Type: new Abstract: Large language models can produce fluent answers that the supplied context does not support. A compact frozen proxy model can detect such answers by rea

Open Benchmark of AI Impact on Humans (ImpactBench): an expert-guided, open platform for the holistic evaluation of AI impact on humans

arXiv:2610.20690v1 Announce Type: cross Abstract: The present work is concerned with how to measure, at scale, the multi-dimensional impact of generative AI models on the individuals who use them. In

When Does Muon Actually Win? A Paired Data-, Time-, and Tuning-Budget Benchmark

arXiv:2610.21555v1 Announce Type: cross Abstract: Muon's gains in data efficiency motivate evaluating its performance under explicit data, time, and tuning budgets. On a single A100 GPU, we compare a

A LoRA is Worth a Thousand Pictures

arXiv:2412.12048v2 Announce Type: replace Abstract: Low-Rank Adaptation (LoRA) has become a standard approach for parameter-efficient fine-tuning of image diffusion models, with over 200K models train

AdaptFuse: Training-Free Sequential Preference Inference via Externalized Bayesian Computation

arXiv:2604.03925v2 Announce Type: replace Abstract: Large language models (LLMs) struggle to accumulate evidence across multiple rounds of user interactions, failing to update their beliefs in a manne

BANGLAPLAN: A Benchmark for Constraint-Based Planning and Decision-Making in Bangla

arXiv:2610.19704v1 Announce Type: new Abstract: Large language models (LLMs) increasingly help users arrange appointments, plan journeys, and allocate limited resources. These tasks require models to

Evaluating LLMs as Agentic Workflow Executors in Real-World Customer Support Skills

arXiv:2610.14346v2 Announce Type: replace Abstract: Enterprise customer-support agents increasingly rely on Large Language Models (LLMs) to execute bounded, tool-using workflows. We study this problem

Fish Audio Drama 3 Technical Report

arXiv:2610.18010v2 Announce Type: replace-cross Abstract: We introduce Fish Audio Drama 3, an open-source speech generation model that turns text into directed performances, built on a 35B-parameter m

Instructions Are Evidence, Not Objectives: Measuring Outcome Alignment of Agents

arXiv:2610.17757v1 Announce Type: new Abstract: Large language model agents can follow complex human instructions to solve real-world tasks. In practice, however, initial instructions are often incomp

Iterate on an LLM, Serve on an SLM

arXiv:2610.14576v1 Announce Type: new Abstract: As frontier LLMs gain more capabilities, the cost to run them also goes up. At the same time, small language models (SLMs) also gain more capabilities b

REPRO: Reflective Evolutionary Prompt Optimizer for Automated LLM Red-Teaming

arXiv:2610.15513v1 Announce Type: cross Abstract: Safety-aligned large language models (LLMs) remain vulnerable to adversarial prompts that bypass their safety training. Existing automated red-teaming

RoTA-Bench: Evaluating 3D Spatial Reasoning through Interactive Projection Alignment

arXiv:2610.17665v2 Announce Type: new Abstract: Can vision-language models turn 2D observations into 3D understanding that supports precise action? This requires inferring object geometry, anticipatin

Spectral-MoE: Heterogeneous Per-Layer Expert Utilization in Dense-to-MoE Conversion

arXiv:2610.19232v1 Announce Type: new Abstract: Large language models impose substantial memory demands and arithmetic costs during inference. Dense-to-mixture-of-experts (MoE) conversion is a model o

The COUNT: Counting N-grams Unlocks Scaling on Host Memory and Training-Free Adaptation

arXiv:2610.20456v1 Announce Type: new Abstract: The scaling relationship of compute and performance for language models (LMs) has been extensively studied; more recently, models are being designed to

ATTUNE: Agentic Throughput Tuning for LLM Training

arXiv:2610.17528v1 Announce Type: cross Abstract: Training recipes are tuned by hand for one model, cluster and workload, and every new model, accelerator, framework version or dataset means tuning ag

14 Oct 2026

Decoupling Knowledge Forgetting and Refusal Learning in MLLM Unlearning

arXiv:2610.14605v1 Announce Type: cross Abstract: Current evaluations of multimodal unlearning typically focus on whether a model stops outputting target information. This surface-level criterion, how

14 Oct 2026

Genesis: Visual Augmentation Primitives for Multimodal Chain-of-Thought Reasoning

arXiv:2610.15565v1 Announce Type: new Abstract: Recent multimodal large language models achieve promising results on visual reasoning tasks, approaching human-level performance on existing STEM benchm