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arXiv:2604.14703v1 Announce Type: new Abstract: Although some existing image manipulation localization (IML) methods incorporate authenticity-related supervision, this information is typically utilize

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The Devil Is in Gradient Entanglement: Energy-Aware Gradient Coordinator for Robust Generalized Category Discovery

DGX agent

arXiv:2604.14176v1 Announce Type: new Abstract: Generalized Category Discovery (GCD) leverages labeled data to categorize unlabeled samples from known or unknown classes. Most previous methods jointly

safetyarxiv-cs-lg

17 Apr 2026

The Fourth Challenge on Image Super-Resolution (imes4) at NTIRE 2026: Benchmark Results and Method Overview

model-releasesarxiv-cs-cv

arXiv:2604.14558v1 Announce Type: new Abstract: This paper presents the NTIRE 2026 image super-resolution (imes4) challenge, one of the associated competitions of the NTIRE 2026 Workshop at CVPR 2026.

The LLM Fallacy: Misattribution in AI-Assisted Cognitive Workflows

arXiv:2604.14807v1 Announce Type: cross Abstract: The rapid integration of large language models (LLMs) into everyday workflows has transformed how individuals perform cognitive tasks such as writing,

safetyarxiv-cs-cl

The Mirror Design Pattern: Strict Data Geometry over Model Scale for Prompt Injection Detection

model-releasesarxiv-cs-ai

arXiv:2603.11875v2 Announce Type: replace-cross Abstract: Prompt injection defenses are often framed as semantic understanding problems and delegated to increasingly large neural detectors. For the fi

The PICCO Framework for Large Language Model Prompting: A Taxonomy and Reference Architecture for Prompt Structure

arXiv:2604.14197v1 Announce Type: new Abstract: Large language model (LLM) performance depends heavily on prompt design, yet prompt construction is often described and applied inconsistently. Our purp

safetyarxiv-cs-cl

The Specification Trap: Why Static Value Alignment Alone Is Insufficient for Robust Alignment

arXiv:2512.03048v4 Announce Type: replace-cross Abstract: Static content-based AI value alignment is insufficient for robust alignment under capability scaling, distributional shift, and increasing au

Theory of Mind in Action: The Instruction Inference Task in Dynamic Human-Agent Collaboration

model-releasesarxiv-cs-cl

arXiv:2507.02935v2 Announce Type: replace Abstract: Successful human-agent teaming relies on an agent being able to understand instructions given by a (human) principal. In many cases, an instruction

Hardware

Thermodynamic Diffusion Inference with Minimal Digital Conditioning

arXiv:2604.14332v1 Announce Type: new Abstract: Diffusion-model inference and overdamped Langevin dynamics are formally identical. A physical substrate that encodes the score function therefore equili

hardwarearxiv-cs-lg

Think in Latent Thoughts: A New Paradigm for Gloss-Free Sign Language Translation

model-releasesarxiv-cs-cv

arXiv:2604.15301v1 Announce Type: new Abstract: Many SLT systems quietly assume that brief chunks of signing map directly to spoken-language words. That assumption breaks down because signers often cr

Three-Phase Transformer

model-releasesarxiv-cs-cl

arXiv:2604.14430v1 Announce Type: new Abstract: We present Three-Phase Transformer (3PT), a residual-stream structural prior for decoder-only Transformers on a standard SwiGLU + RMSNorm + RoPE + GQA b

Threshold Differential Attention for Sink-Free, Ultra-Sparse, and Non-Dispersive Language Modeling

arXiv:2601.12145v2 Announce Type: replace Abstract: Softmax attention struggles with long contexts due to structural limitations: the strict sum-to-one constraint forces attention sinks on irrelevant

Tight Bounds for Learning Polyhedra with a Margin

arXiv:2604.14614v1 Announce Type: cross Abstract: We give an algorithm for PAC learning intersections of k halfspaces with a rho margin to within error arepsilon that runs in time extsf{poly}(k, areps

Local Ai

Tight Sample Complexity Bounds for Best-Arm Identification Under Bounded Systematic Bias

arXiv:2604.14345v1 Announce Type: new Abstract: As search depth increases in autonomous reasoning and embodied planning, the candidate action space expands exponentially, heavily taxing computational

local-aiarxiv-cs-lg

Time-RA: Towards Time Series Reasoning for Anomaly Diagnosis with LLM Feedback

model-releasesarxiv-cs-lg

arXiv:2507.15066v5 Announce Type: replace Abstract: Time series anomaly detection (TSAD) has traditionally focused on binary classification and often lacks the fine-grained categorization and explanat

Timescale Separation Enables Deep Reinforcement Learning Control of Rotating Detonation Engine Mode Transitions

arXiv:2604.14398v1 Announce Type: cross Abstract: Rotating detonation engines (RDEs) are a promising propulsion concept that may offer higher thermodynamic efficiency and specific impulse than convent

agentsarxiv-cs-lg

To See or To Please: Uncovering Visual Sycophancy and Split Beliefs in VLMs

arXiv:2603.18373v2 Announce Type: replace Abstract: When VLMs answer correctly, do they genuinely rely on visual information or exploit language shortcuts? We introduce the Tri-Layer Diagnostic Framew

TokenFormer: Unify the Multi-Field and Sequential Recommendation Worlds

arXiv:2604.13737v1 Announce Type: cross Abstract: Recommender systems have historically developed along two largely independent paradigms: feature interaction models for modeling correlations among mu

researcharxiv-cs-ai

TokenGS: Decoupling 3D Gaussian Prediction from Pixels with Learnable Tokens

arXiv:2604.15239v1 Announce Type: new Abstract: In this work, we revisit several key design choices of modern Transformer-based approaches for feed-forward 3D Gaussian Splatting (3DGS) prediction. We

researcharxiv-cs-cv

TokenLight: Precise Lighting Control in Images using Attribute Tokens

arXiv:2604.15310v1 Announce Type: new Abstract: This paper presents a method for image relighting that enables precise and continuous control over multiple illumination attributes in a photograph. We

researcharxiv-cs-cv

TOPCELL: Topology Optimization of Standard Cell via LLMs

arXiv:2604.14237v1 Announce Type: new Abstract: Transistor topology optimization is a critical step in standard cell design, directly dictating diffusion sharing efficiency and downstream routability.

TopoDIM: One-shot Topology Generation of Diverse Interaction Modes for Multi-Agent Systems

arXiv:2601.10120v2 Announce Type: replace-cross Abstract: Optimizing communication topology in LLM-based multi-agent system is critical for enabling collective intelligence. Existing methods mainly re

agentsarxiv-cs-cl

Topology-Aware Active Learning on Graphs

model-releasesarxiv-cs-lg

arXiv:2510.25892v2 Announce Type: replace Abstract: We propose a graph-topological approach to active learning that directly targets the core challenge of exploration versus exploitation under scarce

Towards a Multi-Embodied Grasping Agent

arXiv:2510.27420v3 Announce Type: replace Abstract: Multi-embodiment grasping focuses on developing approaches that exhibit generalist behavior across diverse gripper designs. Existing methods often l

agentsarxiv-cs-ro

Towards AI-assisted Neutrino Flavor Theory Design

arXiv:2506.08080v2 Announce Type: replace-cross Abstract: Particle physics theories, such as those which explain neutrino flavor mixing, arise from a vast landscape of model-building possibilities. A

agentsarxiv-cs-lg

Towards Bridging the Reward-Generation Gap in Direct Alignment Algorithms

arXiv:2506.09457v3 Announce Type: replace Abstract: Direct Alignment Algorithms (DAAs), such as Direct Preference Optimization (DPO) and Simple Preference Optimization (SimPO), have emerged as efficie

safetyarxiv-cs-cl

Towards Deploying VLA without Fine-Tuning: Plug-and-Play Inference-Time VLA Policy Steering via Embodied Evolutionary Diffusion

arXiv:2511.14178v2 Announce Type: replace Abstract: Vision-Language-Action (VLA) models have demonstrated significant potential in real-world robotic manipulation. However, pre-trained VLA policies st

safetyarxiv-cs-ro

Towards Design Compositing

arXiv:2604.14605v1 Announce Type: new Abstract: Graphic design creation involves harmoniously assembling multimodal components such as images, text, logos, and other visual assets collected from diver

researcharxiv-cs-cv

Towards Faster Language Model Inference Using Mixture-of-Experts Flow Matching

arXiv:2604.15009v1 Announce Type: cross Abstract: Flow matching retains the generation quality of diffusion models while enabling substantially faster inference, making it a compelling paradigm for ge

Towards Fine-grained Temporal Perception: Post-Training Large Audio-Language Models with Audio-Side Time Prompt

arXiv:2604.13715v1 Announce Type: cross Abstract: Large Audio-Language Models (LALMs) enable general audio understanding and demonstrate remarkable performance across various audio tasks. However, the

safetyarxiv-cs-ai

Towards Scalable Lightweight GUI Agents via Multi-role Orchestration

arXiv:2604.13488v1 Announce Type: new Abstract: Autonomous Graphical User Interface (GUI) agents powered by Multimodal Large Language Models (MLLMs) enable digital automation on end-user devices. Whil

safetyarxiv-cs-ai

Towards Trustworthy 6G Network Digital Twins: A Framework for Validating Counterfactual What-If Analysis in Edge Computing Resources

arXiv:2604.14787v1 Announce Type: cross Abstract: Network Digital Twins (NDTs) enable safe what-if analysis for 6G cloud-edge infrastructures, but adoption is often limited by fragmented workflows fro

Towards Verified and Targeted Explanations through Formal Methods

arXiv:2604.14209v1 Announce Type: new Abstract: As deep neural networks are deployed in safety-critical domains such as autonomous driving and medical diagnosis, stakeholders need explanations that ar

Tracking the Temporal Dynamics of News Coverage of Catastrophic and Violent Events

arXiv:2604.14315v1 Announce Type: new Abstract: The modern news cycle has been fundamentally reshaped by the rapid exchange of information online. As a result, media framing shifts dynamically as new

researcharxiv-cs-cl

Trajectory Planning for a Multi-UAV Rigid-Payload Cascaded Transportation System Based on Enhanced Tube-RRT*

arXiv:2604.15074v1 Announce Type: new Abstract: This paper presents a two-stage trajectory planning framework for a multi-UAV rigid-payload cascaded transportation system, aiming to address planning c

safetyarxiv-cs-ro

Applications

Trust and Reliance on AI in Education: AI Literacy and Need for Cognition as Moderators

arXiv:2604.01114v2 Announce Type: replace-cross Abstract: As generative AI systems are integrated into educational settings, students often encounter AI-generated output while working through learning

applicationsarxiv-cs-ai

Tug-of-War within A Decade: Conflict Resolution in Vulnerability Analysis via Teacher-Guided Retrieval-Augmented Generations

arXiv:2604.14172v1 Announce Type: new Abstract: Large Language Models (LLMs) are essential for analyzing and addressing vulnerabilities in cybersecurity. However, among over 200,000 vulnerabilities we

researcharxiv-cs-cl

Applications

TurboTalk: Progressive Distillation for One-Step Audio-Driven Talking Avatar Generation

arXiv:2604.14580v1 Announce Type: new Abstract: Existing audio-driven video digital human generation models rely on multi-step denoising, resulting in substantial computational overhead that severely

applicationsarxiv-cs-cv

TwinOR: Photorealistic Digital Twins of Dynamic Operating Rooms for Embodied AI Research

arXiv:2511.07412v2 Announce Type: replace Abstract: Developing embodied AI for intelligent surgical systems requires safe, controllable environments for continual learning and evaluation. However, saf

Uncovering the Fragility of Trustworthy LLMs through Chinese Textual Ambiguity

model-releasesarxiv-cs-cl

arXiv:2507.23121v2 Announce Type: replace Abstract: In this work, we study a critical research problem regarding the trustworthiness of large language models (LLMs): how LLMs behave when encountering

UniDoc-RL: Coarse-to-Fine Visual RAG with Hierarchical Actions and Dense Rewards

arXiv:2604.14967v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) extends Large Vision-Language Models (LVLMs) with external visual knowledge. However, existing visual RAG systems t

Universal hidden monotonic trend estimation with contrastive learning

arXiv:2210.09817v3 Announce Type: replace Abstract: In this paper, we describe a universal method for extracting the underlying monotonic trend factor from time series data. We propose an approach rel

Tutorials

Unraveling the Mechanism of Drug Binding to SARS-CoV-2 RNA Pseudoknot with Thermodynamics-Driven Machine Learning

arXiv:2604.14906v1 Announce Type: cross Abstract: The SARS-CoV-2 RNA pseudoknot is a promising target for antiviral intervention, as it regulates the efficiency of -1 programmed ribosomal frameshiftin

tutorialsarxiv-cs-lg

Unsupervised feature selection using Bayesian Tucker decomposition

arXiv:2604.14949v1 Announce Type: cross Abstract: In this paper, we proposed Bayesian Tucker decomposition (BTuD) in which residual is supposed to obey Gaussian distribution analogous to linear regres

Unsupervised Learning of Local Updates for Maximum Independent Set in Dynamic Graphs

arXiv:2505.13754v3 Announce Type: replace Abstract: We present the first unsupervised learning model for Maximum-Independent-Set (MaxIS) in dynamic graphs where edges change over time. Our method comb

Unsupervised Skeleton-Based Action Segmentation via Hierarchical Spatiotemporal Vector Quantization

arXiv:2604.15196v1 Announce Type: new Abstract: We propose a novel hierarchical spatiotemporal vector quantization framework for unsupervised skeleton-based temporal action segmentation. We first intr

Local Ai

V-Reflection: Transforming MLLMs from Passive Observers to Active Interrogators

arXiv:2604.03307v2 Announce Type: replace Abstract: Multimodal Large Language Models (MLLMs) have achieved remarkable success, yet they remain prone to perception-related hallucinations in fine-graine

local-aiarxiv-cs-cv

Applications

Variance Computation for Weighted Model Counting with Knowledge Compilation Approach

arXiv:2601.03523v2 Announce Type: replace Abstract: One of the most important queries in knowledge compilation is weighted model counting (WMC), which has been applied to probabilistic inference on va

applicationsarxiv-cs-ai