Search: “models”

Belief-Guided Decision Making with Uncertainty Gating in the Game of Go

arXiv:2607.26946v1 Announce Type: new Abstract: Recent advancements in Computer Go, driven by AlphaZero and MuZero, rely heavily on Monte Carlo Tree Search (MCTS) to correct the errors of the neural n

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Beyond Feeling Better: Capability-Sustaining Emotional Dialogue as a Longitudinal Research Paradigm

DGX agent

arXiv:2607.27851v1 Announce Type: new Abstract: Emotional dialogue research includes two influential strategy traditions. Empathetic dialogue prioritizes understanding a speaker's emotional experience

safetyarxiv-cs-cl

31 Jul 2026

CaM-Wolf: Causal-Aware Multimodal Agents for Social Deduction Games

arXiv:2607.26393v1 Announce Type: new Abstract: Social deduction games (SDGs) such as Werewolf have become challenging testbeds for AI agents. These games require complex social skills such as reasoni

agentsarxiv-cs-ai

Compression-Based Behavioral Similarity for Open-World Sybil Discovery on Ethereum

arXiv:2607.27370v1 Announce Type: new Abstract: Sybil attackers are Blockchain actors that adopt the characteristics of regular users to exploit airdrops or influence governance. Current methods of Sy

Contrastive Reinforced Policy Optimization via Privileged Self-Distillation

arXiv:2607.28026v1 Announce Type: new Abstract: Recent advances in post-training Large Language Models (LLMs) increasingly rely on Reinforcement Learning with Verifiable Rewards (RLVR) or On-Policy Se

DECODE: Tackling Representation and Decision Degradation in Continual AI-Generated Image Detection

arXiv:2607.27882v1 Announce Type: new Abstract: As generative models continue to evolve, AI-generated image detectors must incrementally adapt to emerging generative domains while preserving knowledge

safetyarxiv-cs-cv

Applications

DIPHINE: Diffusion-based Phi-ID Neural Estimator

arXiv:2606.18997v2 Announce Type: replace Abstract: Uncovering the true informational architecture of real-world complex systems requires disentangling how their components uniquely store, redundantly

applicationsarxiv-cs-lg

Do Latent Channels Actually Communicate? A Causal Audit of Latent Multi-Agent LLM

arXiv:2607.26773v1 Announce Type: new Abstract: Latent communication in large language model (LLM)-based multi-agent systems (MAS) transmits continuous internal representations instead of text, but gr

agentsarxiv-cs-ai

Tutorials

Enhancing Scene Transition Awareness in Video Generation via Post-Training

arXiv:2507.18046v2 Announce Type: replace Abstract: Recent advances in AI-generated video have shown strong performance on text-to-video tasks, particularly for short clips depicting a single scene. H

tutorialsarxiv-cs-cv

FADEx: Feature Attribution and Distortion-based Explanation of Dimensionality Reduction

arXiv:2607.27463v1 Announce Type: new Abstract: Dimensionality Reduction (DR) is a fundamental tool for high-dimensional data exploration, reducing the complexity of latent spaces of machine learning

Tutorials

Finding Change in Satellite Archives from Text: How to Combine Before-and-After Images Efficiently

arXiv:2607.28571v1 Announce Type: new Abstract: Operational Earth observation increasingly calls for answering queries such as ``find the image pairs where a new building appeared.'' This means search

tutorialsarxiv-cs-cv

Tutorials

FootprintNet: State-Transition-Guided Dynamic Footprint Learning for Multi-temporal Remote Sensing Change Detection

arXiv:2607.27969v1 Announce Type: new Abstract: Despite substantial progress in remote sensing multi-temporal change detection (MTCD), most existing MTCD methods still represent the dynamic process at

tutorialsarxiv-cs-cv

Functional Cache Grafting: Robust and Rapid Code-Policy Synthesis for Embodied Agents

arXiv:2606.13097v2 Announce Type: replace-cross Abstract: Code-writing large language models (CodeLLMs) generate executable code policies for embodied agents by translating natural language goals and

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GGC: Selective Query Correction for Reliable Text-to-SPARQL Generation

arXiv:2607.28082v1 Announce Type: new Abstract: Large language models (LLMs) have demonstrated strong capabilities in structured query generation, making them a natural choice for Text-to-SPARQL, whic

researcharxiv-cs-cl

GVR-Coder: A Visual-Feedback Framework for Structured SVG Generation in Complex Document and Meeting Scenarios

arXiv:2607.28073v1 Announce Type: cross Abstract: In demanding professional environments and meeting review scenarios, lengthy text often imposes a high cognitive load. To facilitate efficient informa

agentsarxiv-cs-cv

How does downsampling affect needle electromyography signals? A generalisable workflow for understanding downsampling effects on high-frequency time series

arXiv:2601.10191v2 Announce Type: replace Abstract: Automated analysis of needle electromyography (nEMG) signals is emerging as a tool to support the detection of neuromuscular diseases (NMDs), yet th

researcharxiv-cs-ai

HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs

arXiv:2607.27379v1 Announce Type: new Abstract: High-quality, diverse data are vital for large language models (LLMs) but remain scarce and costly. Data synthesis is a viable alternative and succeeds

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Improving Item Discoverability in e-Commerce Search via Related Intent Generation

arXiv:2607.27172v1 Announce Type: cross Abstract: Traditional search systems are optimized to retrieve items that strictly match a query, often prioritizing precision over recall. In e-commerce market

researcharxiv-cs-ai

Integrating Contextual Embeddings into Evaluation of Expressive MIDI Piano Performances

arXiv:2607.27909v1 Announce Type: cross Abstract: Objective evaluation of expressive MIDI piano performances typically relies on attribute statistics such as timing, velocity, and duration of individu

MarkushGlyph and OCSRGlyph: Improved Chemical Structure Recognition

arXiv:2607.28532v1 Announce Type: new Abstract: Chemical structures appear in patents and the scientific literature as images. For programmatic usage, such as indexing in databases or constructing mac

MeshFM: 2D Features Are All You Need for 3D Shape Understanding

arXiv:2607.27592v1 Announce Type: new Abstract: We present MeshFM, an efficient feedforward framework for extracting rich features from 3D inputs. Our method distills 2D features from visual foundatio

More Data, Worse Decisions? Preference Reversals in Neural Networks under Gram Incompatibility

arXiv:2607.27255v1 Announce Type: cross Abstract: Neural networks increasingly combine data across populations, time periods, and operating conditions to improve generalization. This raises a reliabil

MPEcho: A Melody and Phoneme-Aware Generative Framework for Controllable Cover Song Generation

arXiv:2607.26698v1 Announce Type: cross Abstract: Cover song generation (CSG) should preserve the melodic and linguistic content of a reference song while recreating the remaining musical components.

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OneShot: Index-in-Ranking with Neural Scoring for Large-Scale Retrieval

arXiv:2607.27475v1 Announce Type: cross Abstract: In modern recommendation systems, retrieval serves as a primary stage responsible for filtering billions of candidate items down to thousands prior to

Physical prior guided cooperative learning framework for joint turbulence degradation estimation and infrared video restoration

arXiv:2408.04227v2 Announce Type: replace-cross Abstract: Infrared imaging and turbulence strength measurements are in widespread demand in many fields. This paper introduces a Physical Prior Guided C

Real-Time Hard Peak Age-of-Information Safety with No-Regret Learning

arXiv:2607.27626v1 Announce Type: new Abstract: Safety-critical IoT systems such as industrial closed-loop control, V2X coordination, and remote teleoperation require every sensor's peak Age of Inform

ReDiPPO: Reference-Guided Value Calibration and Discrepancy-Aware Token Reweighting for Mathematical Reasoning

arXiv:2607.27631v1 Announce Type: cross Abstract: Reinforcement learning has emerged as an effective paradigm for enhancing the mathematical reasoning capabilities of large language models. Among exis

safetyarxiv-cs-cl

Regularizing modality contribution drift in multimodal continual learning

arXiv:2607.27260v1 Announce Type: new Abstract: Multimodal continual learning (MMCL) aims to learn emerging knowledge from multimodal data while preserving knowledge. To mitigate forgetting, current M

Robust Wavelength Selection for Partial Least Squares Sugar Content Estimation Using Combinatorial Bayesian Optimization

arXiv:2607.27645v1 Announce Type: cross Abstract: Wavelength selection is one of the important preprocessing methods in near-infrared spectroscopy to improve prediction accuracy and interpretability o

Same Branches, Different Trees: A Bifurcation Connectedness Metric for Coronary Artery Segmentation and FFR-CT Decision Agreement

arXiv:2607.28327v1 Announce Type: new Abstract: Fractional flow reserve derived from CT angiography (FFR-CT) simulates flow through a patient-specific vessel model, so its accuracy depends on the conn

Search Strategies for Optimal Classification and Regression Trees

arXiv:2607.28170v1 Announce Type: new Abstract: Optimal decision trees (ODTs) are compact, interpretable machine learning models that globally optimize a given objective, but their scalability remains

Applications

SharedAssembly: A Data Collection Approach via Shared Tele-Assembly

arXiv:2503.12287v2 Announce Type: replace Abstract: High-precision, tight-clearance assembly demonstrations are indispensable for training tactile-aware robotic foundation models, yet their acquisitio

applicationsarxiv-cs-ro

Hardware

Simulation of Surgical Suturing Using Position-Based Dynamics and the Material Point Method for Robot Reinforcement Learning

arXiv:2607.27494v1 Announce Type: new Abstract: Recent advances in robotics research have created a strong demand for high-performance simulators. Surgical robotics simulation faces unique challenges

hardwarearxiv-cs-ro

TIER-MoE: Trust-Informed Expert Routing via Conditional Modality Risk for Multimodal Fusion in Biomedical Classification

arXiv:2607.27289v1 Announce Type: new Abstract: The promise of multimodal fusion lies in combining complementary sources of evidence, yet more evidence does not always yield a better prediction. Recen

TongueReenact: Geometry-Anchored Tongue Synthesis for Face Reenactment

arXiv:2607.28039v1 Announce Type: new Abstract: Modern face reenactment systems achieve impressive pose and expression transfer using geometry-driven representations. However, they largely ignore tong

Applications

Train Small, Deploy Large: Zero-Shot GNN Transfer Through Geometric Renormalization

arXiv:2607.27767v1 Announce Type: new Abstract: Graph neural networks (GNNs) can operate on large graphs but become infrastructure-sensitive at the scale of millions of nodes and typically require sca

applicationsarxiv-cs-lg

Variance-Aware Baselines and Adaptive Learning Rates for Reinforcement Learning with Verifiable Rewards

arXiv:2511.23310v3 Announce Type: replace-cross Abstract: Reinforcement learning with verifiable rewards (RLVR) has emerged as an effective paradigm for post-training large language models, yet the de

VisualRouter: Query-Grounded Visual Sampling for Long Video Understanding

arXiv:2607.28463v1 Announce Type: new Abstract: Large vision-language models (LVLMs) have achieved significant progress in video understanding, yet understanding long videos remains challenging due to

A Compositional Theory of Causally Masked Transformers

arXiv:2607.26988v1 Announce Type: cross Abstract: What types of decision problems can a causally masked, finite-precision transformer solve for inputs of arbitrary length? Existing answers often rely

Adaptive Gradient-Based Methods for a Broader Class of Optimization Problems under Performative Prediction

arXiv:2607.26562v1 Announce Type: cross Abstract: We study optimization under performative prediction, where deploying a model affects the future data distribution. For this setting, several gradient-

Local Ai

Adaptively Robust LLM Monitoring via Activation Watermarking

arXiv:2603.23171v3 Announce Type: replace-cross Abstract: Providers monitor deployed large language models (LLMs) to detect misuse that they cannot prevent. LLM monitoring is deterministic and often o

local-aiarxiv-cs-lg

AI Alignment in Medical Imaging: Unveiling Hidden Biases Through Counterfactual Analysis

arXiv:2504.19621v2 Announce Type: replace Abstract: Machine learning (ML) systems for medical imaging have demonstrated remarkable diagnostic capabilities, but their susceptibility to biases poses sig

Hardware

BATS: Resource-Efficient Volumetric Segmentation with Boundary-Aware Mixed-Resolution Tokens

arXiv:2607.26829v1 Announce Type: new Abstract: Many high-performing volumetric segmentation models maintain dense multi-scale feature maps, leading to high activation memory and inference cost. We pr

hardwarearxiv-cs-cv

Do Methods Support the Claims? Intra-Paper Verification for Peer Review

arXiv:2607.26066v1 Announce Type: new Abstract: The growing volume of scientific submissions has motivated interest in using large language models (LLMs) to assist peer review. Existing automated nove

safetyarxiv-cs-cl

DREvo: Distilling Recalibrated Historical Experience for Harness Self-Evolution

arXiv:2607.26722v1 Announce Type: cross Abstract: Harness plays a critical role in large language model agent performance, and building a high-performing harness requires substantial expert effort. Th

agentsarxiv-cs-lg

Enfold: Folding World-Generator Computation into Predictive Representations for Efficient Embodied Control

arXiv:2607.26657v1 Announce Type: new Abstract: World generative models are typically used through what they produce: a rendered future, a video-conditioned action, or latent context computed by a cos

researcharxiv-cs-ro

Explainable and Resource-Efficient Spatial Reasoning in Multimodal LLMs for Decision-Critical Applications

arXiv:2607.27145v1 Announce Type: new Abstract: As Multimodal Large Language Models (MLLMs) are increasingly deployed in decision-critical pipelines such as robotics, embodied AI, and safety monitorin

safetyarxiv-cs-cv

Local Ai

FakeIDet3-DB: Refining Digital Attacks and Patch Extraction for Secure ID Benchmarking

arXiv:2607.26641v1 Announce Type: new Abstract: Identity document (ID) authentication relies on the structural integrity of complex, high-frequency security patterns. However, advanced Generative AI m

local-aiarxiv-cs-cv