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Using Large Language Models for Idea Generation in Innovation

model-releasesarxiv-cs-cl

arXiv:2607.27553v1 Announce Type: cross Abstract: This research evaluates the efficacy of large language models (LLMs) in generating new product ideas. To do so, we compare three pools of ideas for ne

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VAD: Attributing Visual Evidence for Target Reconstruction in Multimodal On-Policy Distillation

DGX agent

arXiv:2607.28590v1 Announce Type: cross Abstract: Multimodal on-policy distillation (OPD) transfers fine-grained visual knowledge by supervising student-generated trajectories with a privileged-view t

safetyarxiv-cs-cl

31 Jul 2026

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

safetyarxiv-cs-lg

VCP-DCN: Beyond Visual Concealed Property via Depth Collaborative Network for Camouflaged Object Detection

arXiv:2607.27843v1 Announce Type: new Abstract: Camouflaged Object Detection (COD) aims to identify and segment camouflaged objects in complex environments, which are often concealed because their col

local-aiarxiv-cs-cv

VESTIGE: A Knowledge-Guided Masking Strategy for Corruption-Aware Fine-Tuning of Genomic Transformers, Validated on Ancient DNA Reconstruction

arXiv:2607.27712v1 Announce Type: new Abstract: Standard masked-language-model fine-tuning applies a uniform masking probability across every token position, assuming reconstruction difficulty is posi

VETO: Towards Protecting Images From Frontier AI Editing

arXiv:2607.27292v1 Announce Type: new Abstract: The rise of powerful, accessible image-editing models such as FLUX.2 has brought high-fidelity editing within broad reach. Their capabilities now extend

Agents

VideoCoCo: Code-as-CoT for Physically-Consistent Video Generation via an Agentic Dual-Engine System

arXiv:2607.27380v1 Announce Type: new Abstract: Text-to-video models have achieved remarkable visual quality, yet they still struggle to generate physically consistent dynamics because the temporal ev

agentsarxiv-cs-cv

ViewMind3D: Modular View-Aware Inference for Training-Free 3D-QA

arXiv:2607.28442v1 Announce Type: new Abstract: Recent advances in large language models (LLMs) and vision-language models (VLMs) have enabled new possibilities for 3D question answering (3D-QA), a ke

applicationsarxiv-cs-cv

ViP-Rig: Visual-Prompted Controllable Rigging

arXiv:2607.27982v1 Announce Type: new Abstract: Rigging is inherently task-dependent because the same mesh may require different skeletons and deformation behaviors across animation tasks. In practice

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

Weather Emulators at the Frontier of Heat Extremes Predictability

arXiv:2607.28220v1 Announce Type: cross Abstract: Atmospheric predictability declines rapidly beyond the next ten days, such that forecasts at longer lead times primarily convey large-scale trends rat

What Does It Take to Detect an AI Agent? Minimal Feature Sets for Behavioral Detection under Browser Automation

model-releasesarxiv-cs-ai

arXiv:2607.26935v1 Announce Type: new Abstract: Bot detectors deployed at scale treat traffic as binary: human or bot. This assumption breaks when AI agents browse the web through browser automation,

What Is The Performance Ceiling of My Classifier? Utilizing Category-Wise Influence Functions for Pareto Frontier Analysis

arXiv:2510.03950v2 Announce Type: replace Abstract: Data-centric learning seeks to improve model performance from the perspective of data quality, and has been drawing increasing attention in the mach

What Makes Deep Learning Work for Traditional Chinese Medicine Tongue Diagnosis? A Comprehensive Ablation Study

model-releasesarxiv-cs-cv

arXiv:2607.28148v1 Announce Type: new Abstract: Deep learning has shown promise for automated tongue diagnosis in traditional Chinese medicine (TCM), yet the design space remains underexplored. We con

Tutorials

What Makes Graph Unified? Principles and Generative Sliding-Window Transformer for Graph Foundation Models

arXiv:2607.27966v1 Announce Type: new Abstract: Graph Foundation Models (GFMs) have recently emerged as a promising paradigm for general-purpose graph learning, aiming to learn reusable knowledge that

tutorialsarxiv-cs-lg

What to Remove, What to Preserve: Dual-Ambiguity Rectification for All-in-One Image Restoration

arXiv:2607.28526v1 Announce Type: new Abstract: All-in-one image restoration aims to handle diverse degradations within a unified framework. Existing methods commonly encode heterogeneous degradation

When Does Explicit View Routing Work? A Controlled Study of Multi-View Graph-Text Alignment

arXiv:2607.27530v1 Announce Type: new Abstract: Graph-text retrieval typically maps a graph and its description to a single embedding, even when a query concerns only one semantic aspect, such as a cl

safetyarxiv-cs-lg

When Does Muon Help Agentic Reinforcement Learning?

arXiv:2607.16169v3 Announce Type: replace Abstract: Muon is competitive with AdamW in large-scale pre-training, but its operating regime in reinforcement-learning post-training remains unclear. We map

When Robots Exchange Meaning: A Demo of Goal-Oriented Semantic Communications for Collaborative Robotics

arXiv:2607.28256v1 Announce Type: new Abstract: Collaborative robotics is a representative task-oriented 6G use-case, where communication quality should be reflected in mission execution, environment

researcharxiv-cs-ro

When Should AI Follow? Task Structure and Joint Adaptation by Human and AI Agents

arXiv:2504.20903v4 Announce Type: replace-cross Abstract: How should organizations divide and sequence decision tasks between human and artificial agents? We develop a computational model of joint seq

local-aiarxiv-cs-ai

When unlearning is free: leveraging low influence points to reduce computational costs

arXiv:2512.05254v2 Announce Type: replace Abstract: As concerns around data privacy in machine learning grow, the ability to unlearn, or remove, specific data points from trained models becomes increa

Where and When to Commit: Candidate-Aware Decoding for Diffusion Language Models

arXiv:2607.28166v1 Announce Type: new Abstract: Diffusion language models (DLMs) expose a provisional prediction at every denoising step, creating an opportunity for generation-time early exit that st

researcharxiv-cs-cl

WhisperRec: Latent Reasoning for Efficient Foundation Recommendation Models

model-releasesarxiv-cs-ai

arXiv:2607.26621v2 Announce Type: cross Abstract: Large language models (LLMs) have demonstrated strong reasoning capabilities, motivating their adoption as backbones for foundation recommendation mod

Why Are GUI Agents Correct but Late? Decode on the Decision-Time Critical Path, Tested with Pre-Compiled Policy Trees

arXiv:2607.28399v1 Announce Type: new Abstract: Computer-use agents often fail on transient GUI events because they produce the correct action only after the relevant window has already closed. We ide

WIDE: Boosting Adaptive LLM Inference via Token-level Dynamic Width Pruning

arXiv:2607.28418v1 Announce Type: cross Abstract: Pruning is a promising approach for improving the efficiency of LLMs. Existing static structured pruning methods are hardware-friendly and can deliver

applicationsarxiv-cs-cl

Windowed thinning and query complexity for the bouncy particle and Zigzag samplers

arXiv:2607.28413v1 Announce Type: cross Abstract: Let mu(d x)propto e^{-U(x)} d x on R^d, where U is m-strongly convex and L-smooth, and denote by kappa=L/m the condition number. We consider windowed

Wiring diagram extraction and gluing: a case study in classifying figure skating jumps using 3D dataset

arXiv:2607.27598v1 Announce Type: cross Abstract: Hasse clustering is an algorithm that extracts common patterns in sequential data and represents them in graphical forms. As the number of expected cl

Witness Evidence Portfolios: Single-Prefill Risk Detection for Closed Multimodal Answers

arXiv:2607.27667v1 Announce Type: new Abstract: Reliable deployment of multimodal large language models (MLLMs) requires deciding whether a confident visual answer should be trusted, reviewed, or rout

World Action Planner: Generalizable Decision-Making with Action-Conditioned World Models

arXiv:2607.27599v1 Announce Type: cross Abstract: Building generalizable agents for diverse applications remains a fundamental challenge. While imitation learning-based policies succeed in specific tr

safetyarxiv-cs-ro

Would You Walk to the Car Wash? Revealing the Salience Bias of Large Language Models in Commonsense Reasoning

model-releasesarxiv-cs-cl

arXiv:2607.28478v1 Announce Type: new Abstract: As large language models (LLMs) continue to advance in complex reasoning tasks, they have learned to heavily prioritize explicit conditions provided in

Write-Safe Flow Field Mapping under Ambiguous Onboard Sensing and Localization Drift

arXiv:2607.27713v1 Announce Type: new Abstract: Mobile robots can infer local flow structure from onboard sensing, but a locally plausible estimate is not always safe to write into a global map. Simil

local-aiarxiv-cs-ro

X-NavDP: Generalizing Navigation Diffusion Policy to Novel Behavior and Embodiments with Group Q-score Reweighted Matching

arXiv:2607.28560v1 Announce Type: new Abstract: Pretraining navigation diffusion policies rely on large-scale expert demonstrations. These data are typically generated by a fully-informed oracle plann

local-aiarxiv-cs-ro

You Only Look Omni Gradient Backpropagation for Moving Infrared Small Target Detection

arXiv:2511.13013v2 Announce Type: replace Abstract: Moving infrared small target detection is a key component of infrared search and tracking systems, yet it remains extremely challenging due to low s

ZAPs: A Reward Attribution Framework for DeFi Ecosystems with Adversarial-Robust Scoring via Parallel Anomaly Ensemble Detection

arXiv:2607.27859v1 Announce Type: cross Abstract: Incentive programs are central to user acquisition in decentralized finance, but many reward systems rely on raw volume, transaction count, and wallet

Zero-Shot Face-to-Speech Synthesis via Latent Space Adaptation of a Style-Diffusion TTS Model

arXiv:2607.26742v1 Announce Type: cross Abstract: Zero-shot text-to-speech (TTS) clones a voice from a short audio prompt, but this reliance on reference audio is a barrier when only visual informatio

researcharxiv-cs-ai

ZMIS-SAM: Segment Anything Model Enhanced with Wavelet Transform for Zooplankton Microscopy Image Instance Segmentation

arXiv:2607.27585v1 Announce Type: new Abstract: As primary consumers in the marine food chain, zooplankton play a crucial role in maintaining marine ecological balance. However, the Segment Anything M

ZUNA1.1: A more flexible EEG foundation model for Denoising and Super-resolution

arXiv:2607.27308v1 Announce Type: new Abstract: We introduce ZUNA1.1, a 380M-parameter diffusion autoencoder for flexible EEG signal reconstruction. ZUNA1.1 is capable of reconstructing variable lengt

3DGBGS: 3D Granular Ball Gaussian Splatting for Compact Novel View Synthesis

arXiv:2607.26578v1 Announce Type: new Abstract: Three-dimensional Gaussian Splatting (3DGS) enables high-quality real-time novel-view synthesis through explicit Gaussian primitives and differentiable

local-aiarxiv-cs-cv

A Closer Look at Dynamic Scene Graph Generation In the Era of Multimodal Large Language Models

arXiv:2503.15846v2 Announce Type: replace Abstract: Dynamic Scene Graph Generation (DSGG) aims to capture objects and their evolving relations in videos. Despite recent progress, the practicality and

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

A large-scale corpus of religious radio broadcast transcripts from webstream recordings in the United States

arXiv:2607.26249v1 Announce Type: new Abstract: Religious radio is a widespread but understudied form of mass communication in the United States, and content-level analysis of it has been constrained

researcharxiv-cs-cl

A Persona-based Rate Action Index

arXiv:2607.26545v1 Announce Type: cross Abstract: We propose an index for predicting the U.S. Federal Open Market Committee (FOMC) decision to hike/hold/cut the current federal funds target rate based

safetyarxiv-cs-lg

A Picture Says Thousands of Words - Harnessing Dermal Exposure Data from Images through Hybrid Deep Learning for Enhanced Safety Assessment

arXiv:2607.26170v1 Announce Type: new Abstract: This study developed a hybrid computer vision method to quantify exposed skin from images for dermal exposure assessment. Using 170 indoor-painting imag

safetyarxiv-cs-cv

Actions Have Consequences: Detecting Outcome Performativity using Intervention Testing

arXiv:2607.26908v1 Announce Type: new Abstract: In many domains such as Palliative Care, Credit Assignment and Recommender Systems, predictions may causally influence the outcomes they predict. This p

ActSWM: Action-Sensitive World Models for Long-Horizon Planning in Open-World Games

arXiv:2607.26712v1 Announce Type: new Abstract: Latent world models support efficient model-predictive control by optimizing future control sequences in latent space and replanning in a receding-horiz

local-aiarxiv-cs-ro

AdaMARP: An Adaptive Multi-Agent Interaction Framework for General Immersive Role-Playing

model-releasesarxiv-cs-cl

arXiv:2601.11007v2 Announce Type: replace-cross Abstract: LLM role-playing aims to portray arbitrary characters in interactive narratives, yet existing systems often suffer from limited immersion and

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-

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