Search: “framework”

Temporal Policy: History-Initialized Action Generation for Robotic Learning from Demonstration

arXiv:2607.29482v1 Announce Type: new Abstract: By relying on independent couplings from uninformative Gaussian priors, standard diffusion and flow matching models are forced to learn complex, high-co

safetyarxiv-cs-ro

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TextCloak: Thwarting Unauthorized LLM Exploitation via RL-Driven Unlearnable Text

DGX agent

arXiv:2607.28862v1 Announce Type: cross Abstract: The rapid development of Large Language Models (LLMs) has led to significant advances across a wide range of language tasks, while simultaneously rais

safetyarxiv-cs-ai

3 Aug 2026

TFGformer: Multivariate Time Series Forecasting via Time-Frequency Graph Learning and Covariate Fusion

arXiv:2607.29459v1 Announce Type: cross Abstract: Large-scale multivariate time series from heterogeneous IoT sensors demand accurate long-term forecasting for resource scheduling and predictive maint

researcharxiv-cs-ai

Tutorials

Tipping Point Forecasting in Non-Stationary Dynamics on Function Spaces

arXiv:2308.08794v4 Announce Type: replace Abstract: Tipping points are abrupt, drastic, and often irreversible changes in the evolution of non-stationary and chaotic dynamical systems. For instance, i

tutorialsarxiv-cs-lg

Towards White-Box Deep Wireless Sensing

arXiv:2507.21799v2 Announce Type: replace-cross Abstract: The empirical success of deep learning has spurred its application to the radio-frequency (RF) domain, leading to significant advances in Deep

applicationsarxiv-cs-ai

TRACE: High-Fidelity 3D Scene Editing via Tangible Reconstruction and Geometry-Aligned Contextual Video Masking

arXiv:2604.01207v2 Announce Type: replace Abstract: Existing 3D Gaussian Splatting (3DGS) editing methods primarily focus on appearance modification and often struggle to support flexible geometry edi

safetyarxiv-cs-cv

TransGraspNet: Physically and Geometrically Consistent Manipulation of Transparent Labware

arXiv:2607.29567v1 Announce Type: new Abstract: Manipulating transparent laboratory glassware that contains liquid is inherently safety-critical: even small geometric errors can cause unstable grasps

safetyarxiv-cs-ro

Translation with Thought: Difficulty-Adaptive Reasoning via Reinforcement Learning for Multi-Domain Machine Translation

model-releasesarxiv-cs-ai

arXiv:2607.29287v1 Announce Type: cross Abstract: Multi-domain machine translation (MDMT) poses a unique challenge due to varying levels of linguistic complexity across domains. Inspired by human tran

Unified continuous-time q-learning for mean-field game and mean-field control problems

arXiv:2407.04521v3 Announce Type: replace-cross Abstract: This paper studies the continuous-time q-learning in mean-field jump-diffusion models in a setting where the environment simulator does not pr

safetyarxiv-cs-lg

Versatile On-device Adaptation at the Edge by Unifying Few-shot, Zero-shot, Continual, and In-context Learning

arXiv:2607.29353v1 Announce Type: cross Abstract: With the ever-increasing pervasiveness of smart edge devices, the demand is growing for applications that can be tailored to users (e.g., custom keywo

local-aiarxiv-cs-ai

VFAD: Variational Semantic Prompting Meets Frequency-Adaptive Representation Learning for Zero-Shot Anomaly Detection

arXiv:2607.29370v1 Announce Type: new Abstract: Zero-shot anomaly detection (ZSAD) aims to detect and localize anomalies in unseen categories without access to target-specific training data. Although

safetyarxiv-cs-cv

WaMo: Wavelet-Enhanced Multi-Frequency Trajectory Analysis for Fine-Grained Text-Motion Retrieval

arXiv:2508.03343v2 Announce Type: replace Abstract: Text-Motion Retrieval (TMR) aims to retrieve 3D motion sequences semantically relevant to text descriptions. However, matching 3D motions with text

safetyarxiv-cs-cv

Weight-Space Mixture-of-Experts for Implicit Neural Representation Classification

arXiv:2607.29463v1 Announce Type: new Abstract: Implicit Neural Representations (INRs) encode signals as the weights of a coordinate-based neural network and have recently been proposed as an alternat

What Makes a Sale? Simulating End-to-End Seller--Buyer Retail Dynamics with LLM Agents

arXiv:2604.04468v2 Announce Type: replace Abstract: Evaluating retail strategies before deployment is difficult, as outcomes are determined across multiple stages, from seller-side persuasion through

applicationsarxiv-cs-ai

Who Wins Where? Conformal Model Comparison for Local Superiority

arXiv:2607.29053v1 Announce Type: new Abstract: Standard model comparison is global, aggregating losses across the covariate space to declare a single winner. This can obscure heterogeneous performanc

local-aiarxiv-cs-lg

Wrong Code, Right Structure: Learning Netlist Representations from Imperfect LLM-Generated RTL

arXiv:2603.09161v2 Announce Type: replace-cross Abstract: Learning effective netlist representations is fundamentally constrained by the scarcity of labeled datasets, as real designs are protected by

applicationsarxiv-cs-ai

ZeroR@CHiPSAL 2026: Two-Stage Vision-Language Adaptation with Contrastive Learning for Nepali Meme Classification

arXiv:2607.28637v1 Announce Type: new Abstract: This paper presents our system for the CHiPSAL 2026 shared task on multimodal hate speech and sentiment detection in Nepali memes. We address both subta

researcharxiv-cs-cl

4DHumanDiff: Direct Text-to-4DGS Generation for Consistent 360-Degree Dynamic Humans

arXiv:2607.27634v1 Announce Type: new Abstract: Generating high-quality 360-degree dynamic human assets from text prompts is challenging. Existing methods usually synthesize monocular or multi-view vi

A Reference-Free Score for Detecting Silent Reasoning Failures in Large Language Models

arXiv:2607.26102v1 Announce Type: cross Abstract: Mathematical chain of thought (CoT) evaluation is commonly reduced to whether the final answer matches a reference. This conflates producing a correct

researcharxiv-cs-ai

A Sparse Glimpse of the Whole: Train-Free Self-Speculative Decoding

arXiv:2607.27735v1 Announce Type: new Abstract: Speculative decoding alleviates the memory-bandwidth bottleneck in large language model inference, but its acceleration is jointly constrained by drafti

researcharxiv-cs-cl

Accelerating SGDM via Learning Rate and Batch Size Schedules: A Lyapunov-Based Analysis

arXiv:2508.03105v3 Announce Type: replace Abstract: We analyze the convergence behavior of stochastic gradient descent with momentum (SGDM) under dynamic learning-rate and batch-size schedules by intr

researcharxiv-cs-lg

AdaAnchor4D: Anchor-Conditioned Spatiotemporal Feature Aggregation for Monocular UAV 4D Reconstruction

arXiv:2607.28320v1 Announce Type: new Abstract: Monocular UAV videos provide valuable observations for dynamic reconstruction of complex urban scenes. However, such scenes exhibit pronounced spatiotem

AgentMap: Joint Equivalence and Subsumption Discovery for Ontology Matching

model-releasesarxiv-cs-ai

arXiv:2607.27130v1 Announce Type: new Abstract: Ontology matching (OM) has traditionally been formulated as either equivalence discovery or subsumption matching. The existing OM systems identify only

Albilich: Steerable Proof-State Orchestration for LLM-Based Mathematical Research with CAS Integration

model-releasesarxiv-cs-lg

arXiv:2607.27705v1 Announce Type: cross Abstract: Large language models can contribute useful ideas to mathematical research, yet long-horizon proof attempts remain difficult to coordinate, evaluate,

AlphaSchema: Exploring the Space of Trading Semantics for LLM-Based Alpha Mining

arXiv:2607.26642v1 Announce Type: new Abstract: Automated alpha mining has increasingly adopted large language model (LLM) agents for factor generation and iterative discovery. However, existing LLM-b

local-aiarxiv-cs-ai

ARD-REFSM: Enhancing Reflection Symmetry Detection with Asymmetric Denoising and Rotation Equivariance

model-releasesarxiv-cs-cv

arXiv:2607.27927v1 Announce Type: new Abstract: Reflection symmetry detection remains challenging due to interference from asymmetric regions and arbitrary orientations of symmetric patterns. Asymmetr

ARES: Anomaly Recognition Model For Edge Streams

arXiv:2511.22078v2 Announce Type: replace Abstract: Many real-world scenarios involving streaming information can be represented as temporal graphs, where data flows through dynamic changes in edges o

applicationsarxiv-cs-lg

Articulated Object Reconstruction from Rest-State Observation

arXiv:2607.27749v1 Announce Type: new Abstract: Building interactive digital twins requires recovering both 3D geometry and the kinematic structures that govern how objects articulate. Yet existing me

Auditing Question-Order Effects in Large Language Models with the QQ Equality: Mechanism Characterization and a Saturation Caveat

arXiv:2607.17219v2 Announce Type: replace Abstract: Question-order effects in human survey data have been reported to approximately satisfy the QQ (quantum question) equality, a parameter-free predict

Tutorials

AutoPref: Automatic Discovery of Task-Specific Preference Objectives for Neural Combinatorial Optimization

arXiv:2607.27953v1 Announce Type: new Abstract: Combinatorial optimization problems (COPs) underpin many real-world decisions, but their exponentially large search spaces make high-quality solutions c

tutorialsarxiv-cs-lg

Baikal: Structured Search for Deep Research over Data Lakes

arXiv:2607.27726v1 Announce Type: cross Abstract: Deep research over data lakes requires an LLM agent to investigate evidence across thousands of heterogeneous tables and passages to synthesize a repo

BCNet: Bronchus Classification via Structure Guided Representation Learning

model-releasesarxiv-cs-cv

arXiv:2205.06947v3 Announce Type: replace-cross Abstract: CT-based bronchial tree analysis is essential for diagnosing lung and airway diseases, yet automatic bronchus classification remains challengi

Beyond Frame Selection: Generative Latent Evidence Aggregation for Long-Video Understanding

model-releasesarxiv-cs-cv

arXiv:2607.28516v1 Announce Type: new Abstract: Long-video understanding commonly compresses videos into a small set of frames or visual tokens for answer generation. Existing compact pipelines focus

Beyond Sentiment: Structured Information Extraction from Financial News

arXiv:2607.28496v1 Announce Type: new Abstract: Financial sentiment analysis has become a standard component in news-driven stock prediction, yet it reduces rich, multi-dimensional news articles to a

Beyond the Best Teacher: Expanding and Compressing the Reasoning Solution Manifold

arXiv:2607.27770v1 Announce Type: new Abstract: A single reinforcement-learning run can produce a strong reasoner yet an incomplete teacher: it often amplifies only a subset of the valid solution mode

local-aiarxiv-cs-lg

Beyond Visual Ambiguity: Guiding Robust Monocular Depth Estimation in Challenging Scenarios via Detailed Long Captions

arXiv:2607.28285v1 Announce Type: new Abstract: Monocular depth estimation (MDE) faces challenges with non-Lambertian surfaces and adverse weather conditions due to the visual ambiguities inherent in

BioPro: Towards Difference-Aware Gender Fairness for Vision-Language Models

arXiv:2512.00807v2 Announce Type: replace Abstract: Vision-Language Models (VLMs) inherit significant social biases from their training data, notably in gender representation. Current fairness interve

safetyarxiv-cs-ai

Bridging AI and Energy Forecasting: An Autonomous Workflow with Customized Toolkit

model-releasesarxiv-cs-lg

arXiv:2307.07191v3 Announce Type: replace Abstract: Energy forecasting is crucial for the power grid, but fundamentally different from general time series analysis: it highly relies on covariates like

Calibrate Before Reason: Robust Visual Token Reduction against Semantic Drift in VLMs

arXiv:2607.27700v1 Announce Type: new Abstract: Large Vision-Language Models (VLMs) suffer from prohibitive inference overhead due to long sequences of visual tokens. However, existing visual token re

Can Agents Deceive? Evaluating Reasoning and Deception in ParliamentBench using a Social Deduction Game

arXiv:2607.28146v1 Announce Type: new Abstract: As large language models (LLMs) are deployed as agents in high-stakes settings, such as medical and legal systems, understanding their deceptive capabil

Tutorials

Can Large Language Models Execute Parent Orders?

arXiv:2607.28410v1 Announce Type: cross Abstract: Parent-order execution is a core problem in algorithmic trading, where the goal is to split a large order into smaller orders while reducing execution

tutorialsarxiv-cs-cl

Capturing Token Tendencies for Training-Free Token Pruning in Multimodal Large Language Models

arXiv:2607.28341v1 Announce Type: new Abstract: While visual token pruning is essential for efficient Multimodal Large Language Models (MLLMs), existing training-free methods suffer from a critical li

local-aiarxiv-cs-cv

Certifying when decision-time information justifies adaptive experimentation

arXiv:2607.27651v1 Announce Type: new Abstract: Adaptive laboratories choose measurements during experiments, yet most methods begin after adaptation is permitted. We introduce Opportunity-aware Polic

safetyarxiv-cs-lg

CLAM: Continuous Latent Action Models for Robot Learning from Unlabeled Demonstrations

arXiv:2505.04999v2 Announce Type: replace-cross Abstract: Learning robot control policies from demonstrations typically requires action-labeled expert data, which is expensive to collect through teleo

applicationsarxiv-cs-lg

ClawTrack: Towards Trace-Level Evaluation and Improvement of Real-World Autonomous Agents

model-releasesarxiv-cs-lg

arXiv:2607.28037v1 Announce Type: new Abstract: As LLM-based agents are deployed in complex, multi-step workflows, a critical evaluation gap has emerged: most existing benchmarks judge only final outc

Cocktail-Talker: Multi-Speaker Dialog Modeling in Noisy Social Environments with Turn Action GRPO

arXiv:2607.27756v1 Announce Type: cross Abstract: Spoken dialog systems are typically designed for clean, dyadic interactions in which a single user and an assistant take turns speaking. Real-world so

applicationsarxiv-cs-cl

Compact Task-Aligned Imitation Learning for Laboratory Automation

arXiv:2603.01110v2 Announce Type: replace Abstract: Robotic laboratory automation has traditionally relied on carefully engineered motion pipelines and task-specific hardware interfaces, resulting in

local-aiarxiv-cs-ro

Hardware

Complementary Matrix-Gated QKAN Fast-Weight Programmers for Quantum Dynamics Forecasting

arXiv:2607.27945v1 Announce Type: cross Abstract: Sequence models must decide what to write into memory and what to retain. In quantum and quantum-inspired sequence learning, nonlinear recurrent updat

hardwarearxiv-cs-lg