Search: “inference”

Autoregressive Boltzmann Generators

arXiv:2606.27361v1 Announce Type: cross Abstract: Efficient sampling of molecular systems at thermodynamic equilibrium is a hallmark challenge in statistical physics. This challenge has driven the dev

Beyond the Hard Budget: Sparsity Regularizers for More Interpretable Top-k Sparse Autoencoders

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DGX agent

arXiv:2606.27321v1 Announce Type: cross Abstract: Sparse autoencoders (SAEs) have become a leading tool for interpreting the representations of vision foundation models, decomposing their polysemantic

researcharxiv-cs-ai

26 Jun 2026

Cross-Head Attention Uplift Network with Inverse Propensity Score under Unobserved Confounding

arXiv:2606.27114v1 Announce Type: new Abstract: Uplift modeling, crucial for estimating individual treatment effects (ITE), faces dual challenges: flexibly leveraging inter-group similarity to enhance

safetyarxiv-cs-lg

CSU-PCAST: A Dual-Branch Transformer Framework for medium-range ensemble Precipitation Forecasting

arXiv:2510.20769v2 Announce Type: replace-cross Abstract: Accurate medium-range precipitation forecasting is essential for hydrometeorological risk management but remains challenging for both numerica

safetyarxiv-cs-lg

DinoLink: A Token-Centric Representation Compression Framework for Bandwidth-Constrained Collaborative V2X Perception

arXiv:2606.26398v1 Announce Type: new Abstract: High-precision remote perception is often hindered by the severe bandwidth constraints of Vehicle-to-Everything (V2X) networks. We propose extit{DinoLin

Local Ai

Do Safety Guardrails Need to Reason? LeanGuard: A Fast and Light Approach for Robust Moderation

arXiv:2606.26686v1 Announce Type: new Abstract: In order to screen a prompt or a response, the recent guardrail methods generate a chain-of-thought (CoT) before they issue a verdict. This design follo

local-aiarxiv-cs-ai

Local Ai

Dot-Flik: A Scalable Edge AI Architecture for Distributed Insect Monitoring

arXiv:2606.26121v1 Announce Type: cross Abstract: Global insect population declines necessitate scalable, continuous monitoring systems, yet existing vision-based solutions remain constrained by high

local-aiarxiv-cs-ai

E-TTS: A New Embodied Test-Time Scaling Framework for Robotic Manipulation

arXiv:2606.27268v1 Announce Type: cross Abstract: Recently, a few works have made early attempts to study test-time scaling for embodied tasks. However, two major challenges remain unsolved: (1) reaso

Equivariance and Augmentation for Bayesian Neural Networks

arXiv:2606.26273v1 Announce Type: new Abstract: Symmetries are important for many deep learning tasks, ranging from applications in the sciences to medical imaging. However, there is an ongoing debate

tutorialsarxiv-cs-lg

Forget, Anticipate and Adapt: Test Time Training for Long Videos

arXiv:2606.26515v1 Announce Type: new Abstract: Test Time Training (TTT) is a mechanism in which a model adapts to an incoming test-sample by performing some self-supervised (SSL) task and updating it

tutorialsarxiv-cs-cv

GeMoE: Gating Entropy is All You Need for Uncertainty-aware Adaptive Routing in MoE-based Large Vision-Language Models

model-releasesarxiv-cs-cv

arXiv:2606.26287v1 Announce Type: new Abstract: With the increase in model parameters and training data, the instruction following and generalization capabilities of Large VisionLanguage Models (LVLMs

Implementation of reinforcement learning in chemical reaction networks: application to phototaxis as curiosity-driven exploration

arXiv:2606.26168v1 Announce Type: new Abstract: Living systems navigate environments using noisy and incomplete sensory signals. In unicellular algae, phototaxis is often modeled as a mechanistic run-

Improving Vision-Language-Action Model Fine-Tuning with Structured Stage and Keyframe Supervision

arXiv:2606.26801v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models have shown strong potential for generalizable robotic manipulation. During fine-tuning, however, action supervisio

safetyarxiv-cs-cv

In-Context Model Predictive Generation: Open-Vocabulary Motion Synthesis from Language Models to Physics

arXiv:2606.26981v1 Announce Type: cross Abstract: Synthesizing human motion from textual descriptions is essential for immersive digital applications, yet existing methods face a persistent trade-off

Local Ai

Joint Reward Modeling: Internalizing Chain-of-Thought for Efficient Visual Reward Models

arXiv:2602.07533v2 Announce Type: replace Abstract: Reward models are critical for reinforcement learning from human feedback, as they determine the alignment quality and reliability of generative mod

local-aiarxiv-cs-ai

LearniBridge: Learnable Calibration of Feature Caching for Diffusion Models Acceleration

arXiv:2606.26778v1 Announce Type: new Abstract: Diffusion Transformers (DiTs) have driven substantial progress in image and video generation but suffer from prohibitive computational costs. Feature ca

Learning Long-Range Dependencies with Temporal Predictive Coding

arXiv:2602.18131v2 Announce Type: replace Abstract: Temporal Predictive Coding provides a layer-local, parallelisable mechanism for learning in recurrent systems, making it an attractive candidate for

Learning to Fold: prizewinning solution at LeHome Challenge 2026 (1st place online, 2nd offline)

arXiv:2606.27163v1 Announce Type: cross Abstract: I describe my solution to the LeHome Challenge 2026, an ICRA 2026 competition on bimanual garment folding. The system placed 1st of 62 teams in the on

LiMoDE: Rethinking Lifelong Robot Manipulation from a Mixture-of-Dynamic-Experts Perspective

arXiv:2606.26183v1 Announce Type: cross Abstract: Building a generalist robot that can leverage prior knowledge for continuous task adaptation remains a significant challenge. Previous works alleviate

LISA: Likelihood Score Alignment for Visual-condition Controllable Generation

arXiv:2606.27192v1 Announce Type: new Abstract: The prevalent dual-branch paradigm, i.e., training a side network to encode visual conditions and fusing its intermediate-layer features to a frozen pre

safetyarxiv-cs-cv

LogicIR: Logic Gate Networks for Image Restoration

arXiv:2606.26609v1 Announce Type: new Abstract: Image restoration aims to reconstruct high-quality images from degraded low-quality inputs. As the computational demands of image restoration models con

MAVFusion: Efficient Infrared and Visible Video Fusion via Motion-Aware Sparse Interaction

arXiv:2604.01958v2 Announce Type: replace Abstract: Infrared and visible video fusion combines the object saliency from infrared images with the texture details from visible images to produce semantic

MinGram: A Minimalist Unigram Tokenizer with High Compression and Competitive Morphological Alignment

arXiv:2606.27019v1 Announce Type: new Abstract: The Unigram tokenizer uses an elegant representation which makes it straightforward to edit vocabularies, but its training is comparatively heavy and co

Neural Texture Compression using Hypernetworks

arXiv:2606.26913v1 Announce Type: cross Abstract: Recent work on neural texture compression has demonstrated that it is possible to learn small, per-material texture representations (composed of laten

tutorialsarxiv-cs-cv

Neural Voxel Dynamics: Learning Implicit 3D Physics via Volumetric Feature Advection

arXiv:2606.26410v1 Announce Type: new Abstract: We present a self-supervised framework for learning implicit 3D physical dynamics directly from video-derived supervisory signals. While current generat

tutorialsarxiv-cs-cv

Hardware

OctoSense: Self-Supervised Learning for Multimodal Robot Perception

arXiv:2606.27317v1 Announce Type: new Abstract: We present OctoSense, an open-source sensor platform with stereo RGB and event cameras, LiDAR, a thermal camera, an inertial measurement unit, RTK-corre

hardwarearxiv-cs-cv

OI-Bench: An Option Injection Benchmark for Evaluating LLM Susceptibility to Directive Interference

model-releasesarxiv-cs-cl

arXiv:2601.13300v2 Announce Type: replace Abstract: Benchmarking large language models (LLMs) is critical for understanding their capabilities, limitations, and robustness. In addition to interface ar

OpenRCA 2.0: From Outcome Labels to Causal Process Supervision

arXiv:2606.27154v1 Announce Type: new Abstract: Root cause analysis (RCA) poses a holistic test of LLM agentic capabilities, such as long-context understanding, multi-step reasoning, and tool use. How

Overcoming State Inertia: Minimally Invasive Temporal Alignment for Evolving Contexts

arXiv:2512.03704v3 Announce Type: replace Abstract: Long-context dialogue systems suffer from state inertia, where models over-attend to history and fail to adapt to evolving intents. We demonstrate t

Paved with True Intents: Intent-Aware Training Improves LLM Safety Classification Across Training Regimes

arXiv:2606.27210v1 Announce Type: new Abstract: We argue that safety classifiers should model user intent as an explicit signal between the prompt and the final label. To study this, we introduce AIMS

Perception, Verdict, and Evolution: Hindsight-Driven Self-Refining Forensics Agent for AI-Generated Image Detection

arXiv:2606.26552v1 Announce Type: cross Abstract: The rapid advancement of generative models presents a significant challenge to existing deepfake detection methods, particularly given the widespread

Applications

Pianist Transformer: Towards Expressive Piano Performance Rendering via Scalable Self-Supervised Pre-Training

arXiv:2512.02652v2 Announce Type: replace-cross Abstract: Existing methods for expressive music performance rendering, a conditional generation task that aims to generate a human-like performance from

applicationsarxiv-cs-ai

scBench-Long: Verifiable Benchmarking of Long-Horizon Single-Cell Biology

arXiv:2606.26563v1 Announce Type: cross Abstract: Single-cell studies require analysts to convert raw measurements into specific biological claims through multi-step workflows and integration of metad

SpaceRipple: Lightweight Semantic Delivery for Mission-Oriented LEO Earth Observation Satellite Networks

arXiv:2606.26559v1 Announce Type: cross Abstract: Earth observation satellite networks generate massive volumes of high-resolution imagery, whereas inter-satellite and downlink resources remain limite

researcharxiv-cs-ai

Unsupervised Memory-Enhanced Video Transformers: Obstacle Detection for Autonomous Agricultural Rover

arXiv:2606.26151v1 Announce Type: cross Abstract: While autonomous rovers have become indispensable to precision farming, achieving consistent operational safety remains a critical challenge. Conventi

Use What You Know: Causal Foundation Models with Partial Graphs

arXiv:2602.14972v2 Announce Type: replace Abstract: Estimating causal quantities traditionally relies on bespoke estimators tailored to specific assumptions. Recently proposed Causal Foundation Models

researcharxiv-cs-lg

Visual-OPSD: Cross-Modal On-Policy Self-Distillation for Efficient Unified Multimodal Reasoning

arXiv:2606.18974v2 Announce Type: replace Abstract: Unified multimodal models (UMMs) interleave generated ''visual thoughts'' (VTs) with text reasoning to improve spatial tasks. This incurs roughly an

safetyarxiv-cs-cv

VoiceTTA: Enhancing Zero-Shot Text-to-Speech via Reinforcement Learning-Based Test-Time Adaptation

arXiv:2606.26534v1 Announce Type: cross Abstract: Recently, zero-shot text-to-speech (TTS) has enabled high-fidelity and expressive speech synthesis, but it often fails to imitate unseen speaking styl

researcharxiv-cs-ai

When Does Quality-Aware Multimodal Fusion Matter? A Leakage-Safe Diagnostic for Decision-Level Dependence

arXiv:2606.26473v1 Announce Type: new Abstract: Many multimodal systems estimate the reliability of each modality and weight their contributions to the final prediction. However, it remains unclear wh

researcharxiv-cs-lg

When to Write and When to Suppress: Route-Specialized Dual Adapters for Memory-Assisted Knowledge Editing

arXiv:2606.14668v3 Announce Type: replace Abstract: Knowledge editing systems must update selected facts while preserving nearby but irrelevant behavior. This paper studies this problem in a memory-as

A Hybrid CNN-LSTM Intrusion Detection Framework for Cybersecurity in Smart Renewable Energy Grids

arXiv:2606.25200v1 Announce Type: new Abstract: The accelerated digitalization of renewable energy smart grids through IoT sensors, AMI, and SCADA systems has significantly expanded the attack surface

Agents

AeroCast: Probabilistic 3D Trajectory Prediction for Non-Cooperative Aerial Obstacles via Transformer-MDN Architecture

arXiv:2606.25122v1 Announce Type: cross Abstract: Autonomous aerial vehicles operating in shared airspace must predict the future positions of non-cooperative obstacles to plan evasive maneuvers befor

agentsarxiv-cs-lg

Agents

AgentOdyssey: Open-Ended Long-Horizon Text Game Generation for Test-Time Continual Learning Agents

arXiv:2606.24893v1 Announce Type: new Abstract: For agents to learn continuously from interaction with the world at test time, they must be able to explore effectively, acquire new world knowledge and

agentsarxiv-cs-cl

AIChilles: Automatically Uncovering Hidden Weaknesses in AI-Evolved Systems

arXiv:2606.15834v2 Announce Type: replace Abstract: The computer systems community has recently seen growing interest in AI-driven system evolution, where AI agents iteratively rewrite systems. Framew

An Empirical Study of Many-Shot In-Context Learning for Machine Translation of Low-Resource Languages

arXiv:2604.02596v3 Announce Type: replace Abstract: In-context learning (ICL) allows large language models (LLMs) to adapt to new tasks from a few examples, making it promising for languages underrepr

researcharxiv-cs-cl

Approximate Structured Diffusion for Sequence Labelling

arXiv:2606.18856v2 Announce Type: replace Abstract: Sequence labelling, a core task of Natural Language Processing (NLP), consists in assigning each token of an input sentence a label. From a Machine

researcharxiv-cs-cl

ASAP: Agent-System Co-Design for Wall-Clock-Centered Auto HPO Research for ML Experiments

arXiv:2606.25207v1 Announce Type: cross Abstract: Hyperparameter Optimization (HPO) is essential for maximizing machine learning model performance, and its core challenge is sample efficiency: finding

Agents

ASSCG: Just-Right Gating over Chattering for Fast-Slow LLM Planning in Autonomous Driving

arXiv:2606.25509v1 Announce Type: cross Abstract: Large language models (LLMs) can improve autonomous driving planning but are costly to query online, and existing fast-slow planners often rely on han

agentsarxiv-cs-cv