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arXiv:2607.05850v1 Announce Type: new Abstract: Deep neural networks trained with Empirical Risk Minimization (ERM) often fail under distribution shifts because they exploit spurious correlations betw

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Breaking Structural Isolation: Scalable Graph Clustering via Community-Aware Sampling and Structural Entropy

DGX agent

arXiv:2607.05469v1 Announce Type: cross Abstract: Unsupervised graph clustering is a fundamental technique for uncovering underlying semantic patterns in large-scale networks. Although Graph Contrasti

model-releasesarxiv-cs-ai

8 Jul 2026

Breaking the Likelihood Trap: Variance-Calibrated Modulation for Large Language Model Decoding

arXiv:2606.22511v2 Announce Type: replace Abstract: In open-ended generation, LLMs frequently fall into the 'likelihood trap', marked by repetitive degeneration and vocabulary dullness, creating a dis

researcharxiv-cs-cl

Bridging Diffusion Pruning and Step Distillation with Teacher-Aligned Repair

arXiv:2607.06335v1 Announce Type: new Abstract: Diffusion models generate high-quality images, but their inference cost comes from two sources: large denoising networks and repeated denoising steps. E

safetyarxiv-cs-cv

Bridging Physical Reasoning and Task Generalization via Visual Action Outcome Reasoning Alignment

arXiv:2607.06522v1 Announce Type: new Abstract: Vision-language models (VLMs) struggle to generalize in interactive physical reasoning, particularly under unseen tasks and environments. Two key failur

safetyarxiv-cs-ai

Broken Ergodicity and the Violation of the Fluctuation-Dissipation Theorem Lead to Generalization Beyond Overfitting in Machine Learning

arXiv:2607.04135v1 Announce Type: cross Abstract: The remarkable ability of modern neural networks to generalize improves with increasing network capacity, even when the number of model parameters or

researcharxiv-cs-lg

CAIRN: Cross-Room 3D Scene Understanding with Topology-Aware Large Multimodal Models

model-releasesarxiv-cs-cv

arXiv:2607.06534v1 Announce Type: new Abstract: Existing 3D scene-grounded Large Language Models (3D-LLMs) focus on answering questions grounded in simplified single-room 3D scenes, lacking the abilit

Calf-Integrated Arms for Bimanual Quadruped Loco-Manipulation

arXiv:2607.06186v1 Announce Type: new Abstract: Most quadruped loco-manipulation designs trade manipulation capability against stance. A trunk-mounted arm sits high and usually carries a single arm; u

agentsarxiv-cs-ro

CANONIC: Governance Is Compilation

arXiv:2607.05410v1 Announce Type: cross Abstract: We present CANONIC: governed intelligence that compiles digital artifacts into an evidence ledger at scale. Large language models generate prose faste

Tutorials

Canopy: A Heterograph Foundation Model for Metabolic Engineering

arXiv:2607.06224v1 Announce Type: new Abstract: Designing microbial strains that produce high-value chemicals at commercially viable titers remains a central challenge in metabolic engineering. Existi

tutorialsarxiv-cs-lg

CanvasAgent: Enabling Complex Image Creation and Editing via Visual Tool Orchestration

arXiv:2607.05465v1 Announce Type: cross Abstract: Complex image creation and editing often require more than a single generation or editing model. A user request may involve synthesizing images, local

Catalyst Papers in Artificial Intelligence Research: A Landscape on ICLR from 2017 to 2025

arXiv:2607.05401v1 Announce Type: cross Abstract: A small number of methodological contributions, including word2vec, the Transformer, large-scale pre-training, and reinforcement learning from human f

Applications

CCBENCH: Assessing LLM Cultural Competence via Implicitly Signaled Norms using Health Queries

arXiv:2607.05405v1 Announce Type: cross Abstract: To interact with users fairly and without stereotyping, AI models must display cultural competency, i.e., the ability to infer and adapt to a user's i

applicationsarxiv-cs-ai

Channel-wise Retrieval for Multivariate Time Series Forecasting

arXiv:2604.05543v2 Announce Type: replace Abstract: Multivariate time series forecasting often struggles to capture long-range dependencies due to fixed lookback windows. Retrieval-augmented forecasti

researcharxiv-cs-lg

Local Ai

CHARLIE: An On-Premise Multi-Agent Retrieval-Augmented Generation System for Evidential Reasoning in Forensic Science

arXiv:2607.05428v1 Announce Type: cross Abstract: We present Charlie, an on-premise multi-agent Retrieval-Augmented Generation (RAG) system for structured evidential processing in digital forensic env

local-aiarxiv-cs-ai

Choose What to Observe: Task-Aware Semantic-Geometric Representations for Visuomotor Policy

arXiv:2603.07875v2 Announce Type: replace Abstract: Visuomotor policies learned from demonstrations often overfit to nuisance visual factors in raw RGB observations, resulting in brittle behavior unde

safetyarxiv-cs-ro

Classification of Financial Data Using Quantum Support Vector Machine

model-releasesarxiv-cs-lg

arXiv:2412.10860v2 Announce Type: replace-cross Abstract: Quantum Support Vector Machine is a kernel-based approach to classification problems. We study the applicability of quantum kernels to financi

Clustered Codebook Quantization for 2D Gaussian-based Image Compression

model-releasesarxiv-cs-cv

arXiv:2607.05667v1 Announce Type: new Abstract: Gaussian-based image representations effectively model image content using compact parametric primitives while preserving high visual fidelity, yet stor

Clustering-Embedded Model Predictive Path Integral Control: Avoiding Averaging-Induced Failure and Enabling Efficient Cluster Selection for Dynamic Obstacles

arXiv:2607.06499v1 Announce Type: new Abstract: With the widespread availability of parallel computing hardware, sampling-based motion planning methods such as Model Predictive Path Integral (MPPI) co

hardwarearxiv-cs-ro

CMDR: Contextual Multimodal Document Retrieval

arXiv:2607.05927v1 Announce Type: cross Abstract: Multimodal document retrieval aims to retrieve relevant pages while preserving both textual and visual content from the original document. However, ex

Co-STAR: Cognitive Stimulation Therapy by an Autonomous Robot for Dementia -- A One-Week In-Home Study

arXiv:2607.05709v1 Announce Type: new Abstract: Cognitive therapies have been shown to enhance the quality of life and well-being of people living with dementia (PwDs). However, their use remains limi

agentsarxiv-cs-ro

Complementary Roles of Image Classification and Vessel Segmentation in AI-Based Screening for Retinopathy of Prematurity Plus Disease in a Kenyan Preterm Cohort

arXiv:2607.05825v1 Announce Type: cross Abstract: Background. Retinopathy of prematurity (ROP) is a preventable cause of childhood blindness, with rising burden in low- and middle-income countries whe

Conformal Prediction Sets for Instance Segmentation

model-releasesarxiv-cs-cv

arXiv:2602.10045v2 Announce Type: replace Abstract: Current instance segmentation models achieve high performance on average predictions, but lack principled uncertainty quantification: their outputs

Tutorials

Contextual Procurement Auctions with Bandit Learning

arXiv:2607.05813v1 Announce Type: cross Abstract: We study repeated contextual procurement auctions in which the platform must learn context-dependent product values from bandit feedback. We give an e

tutorialsarxiv-cs-lg

Contrastive Predictive Coding with Compression for Enhanced Channel State Feedback in Wireless Networks

arXiv:2607.05419v1 Announce Type: cross Abstract: Accurate and timely channel state information (CSI) is essential for next-generation wireless systems, yet existing works treat CSI compression and CS

Controlling Tool Use with Heading-Specific Activation Steering

arXiv:2607.05790v1 Announce Type: new Abstract: Tool-augmented large language models extend their capabilities beyond parametric knowledge through external tools, but tend to invoke them unnecessarily

safetyarxiv-cs-ai

CoPiT: Cognitive Pivot Translation for Digraphic Low-Resource Mongolian in the Traditional Script

model-releasesarxiv-cs-cl

arXiv:2607.05849v1 Announce Type: new Abstract: Low-resource languages remain challenging for machine translation, and Mongolian is a representative case. As a digraphic language, Mongolian is written

Cross-Contextual Vision-Language Adaptation with LoRA for Personalized Severe Adverse Event Detection in Clinical Wound Monitoring

arXiv:2607.05625v1 Announce Type: new Abstract: Wound monitoring is a critical yet underserved clinical challenge, where timely identification of severe adverse events (SAEs) such as infection, tissue

safetyarxiv-cs-cv

CSTutorBench: Benchmarking Small Language Models as Tutors for Block-Based Programming

arXiv:2607.05571v1 Announce Type: new Abstract: Large language models are increasingly explored as AI tutors, yet deploying them in K-12 settings raises concerns around privacy, cost, and reliance on

CurateEvo: Data-Curation Evolving for Agentic Post-Training

arXiv:2607.06140v1 Announce Type: new Abstract: Large language model (LLM) agents require post-training methods that can improve long-horizon decision making from environment feedback. However, existi

agentsarxiv-cs-cl

Danus: Orchestrating Mathematical Reasoning Agents with Fact-Graph Memory

arXiv:2607.06447v1 Announce Type: new Abstract: Recent LLM-based mathematical reasoning agents have begun to tackle research-level problems and, in several cases, have contributed to the resolution of

Data Analysis in the Wild: Benchmarking Large Language Models Against Real-World Data Complexities

arXiv:2607.06482v1 Announce Type: cross Abstract: Current benchmarks for evaluating Large Language Models (LLMs) in data analysis often fail to reflect real-world settings. They typically focus on fac

Applications

Data-dependent Evaluations for Budgeted Submodular Maximization

arXiv:2607.05759v1 Announce Type: cross Abstract: Submodular maximization is an important building block for developing algorithms in many areas such as machine learning and data mining. Due to the NP

applicationsarxiv-cs-ai

DBNN: Neural Spike Classification Using a Deep Binarized Neural Network

arXiv:2607.05590v1 Announce Type: cross Abstract: Implantable brain-computer interfaces require on-node spike sorting to reduce telemetry bandwidth and power while maintaining reliable neural decoding

hardwarearxiv-cs-lg

Decision-Focused Scenario Generation and Selection for Efficient and Robust Grid Dispatch

arXiv:2607.05830v1 Announce Type: cross Abstract: The increasing uncertainty from flexible demand and renewable generation has made distributionally robust optimization (DRO) an important tool for rob

Decision Protocols in Multi-Agent Large Language Model Conversations

arXiv:2607.05477v1 Announce Type: cross Abstract: Improving the task performance of Large Language Models (LLMs) is essential, yet scaling these models faces significant challenges such as diminishing

Decoding the Multimodal Mind: Generalizable Brain-to-Text Translation via Multimodal Alignment and Adaptive Routing

model-releasesarxiv-cs-cl

arXiv:2505.10356v3 Announce Type: replace Abstract: Decoding language from the human brain remains a grand challenge for Brain-Computer Interfaces (BCIs). Current approaches typically rely on unimodal

Decoupled Single-Mask Annotation Noise Detection via Cross-Sectional Patch Self-Consistency

arXiv:2607.05965v1 Announce Type: cross Abstract: Vascular computed tomography datasets are commonly annotated only once per scan, yielding the pervasive yet under addressed problem of single mask ann

Deep Neural Variation Spaces: A Unifying Perspective on Depth and Complexity

model-releasesarxiv-cs-lg

arXiv:2607.05546v1 Announce Type: cross Abstract: We develop a unified function space theory of deep fully connected neural networks. Functions in our spaces are defined recursively as ell^1-bounded l

Deep Reinforcement Learning for Dynamic Battery Management of Autonomous Order Pickers

model-releasesarxiv-cs-lg

arXiv:2607.05683v1 Announce Type: new Abstract: Battery charging of Autonomous Mobile Robots (AMRs) in warehouses is a critical operational challenge that heavily impacts both order processing times a

Deep Reinforcement Learning for Dynamic Origin-Destination Matrix Estimation in Microscopic Traffic Simulations Considering Credit Assignment

arXiv:2511.06229v3 Announce Type: replace Abstract: This paper focuses on dynamic origin-destination matrix estimation (DODE), a crucial calibration process necessary for the effective application of

safetyarxiv-cs-lg

Delay-Aware Active Triangulation with Uncertainty-Driven Multi-Agent Reinforcement Learning for Counter-UAS

arXiv:2607.05957v1 Announce Type: new Abstract: Multi-agent active visual triangulation enables precise 3D localization of aerial targets by coordinating mobile observers with controllable cameras. Ho

agentsarxiv-cs-ro

Demonstrating TOFFEE: A Learned System for Synthesizing Data Agent Trajectories at Scale

arXiv:2607.06233v1 Announce Type: new Abstract: LLM-powered data agents are playing an increasingly important role in data-driven decision making. However, existing data agents struggle to generalize

Depression Symptoms and Relational Patterns in 187k ChatGPT Histories

arXiv:2607.05685v1 Announce Type: cross Abstract: Large language models are increasingly used as private, always-available conversational systems, but little is known about how people with depressive

DepthWeave-KV: Token-Adaptive Cross-Layer Residual Factorization for Long-Context KV Cache Compression

arXiv:2607.06523v1 Announce Type: new Abstract: Long-context language model inference is increasingly limited by the memory bandwidth and capacity required to store key-value caches, yet existing comp

hardwarearxiv-cs-ai

DeSeG: Decoupling Semantic Intent and Geometric Constraints for Physically Plausible Human-Scene Interaction

arXiv:2607.05787v1 Announce Type: new Abstract: Synthesizing physically plausible human-scene interactions (HSI) remains a critical challenge in computer vision and the development of human avatars. A

safetyarxiv-cs-cv

Design-CP: Context Parallelism for Design of Protein Nanoparticles

arXiv:2607.05439v1 Announce Type: new Abstract: Many all-atom generative protein models can in principle design large multimeric complexes by jointly modelling all chains, but their quadratic token- a

hardwarearxiv-cs-lg

Designing Maintainable Hybrid Generative Systems: A Quantum-Inspired Approach to Automated Music Harmony Generation

arXiv:2607.06296v1 Announce Type: cross Abstract: This paper presents the design and evaluation of a maintainable hybrid generative architecture for automated music harmony generation from melody. The