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arXiv:2606.20002v2 Announce Type: replace-cross Abstract: This work presents a general framework for training large language models (LLMs) to 'Connect the Dots' (CoD), a meta-capability required by lo

agentsarxiv-cs-cl

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Hardware

Connected Content Retriever: Dense Graph Edge Features Powering Pre-Ranking at LinkedIn

DGX agent

arXiv:2609.22441v1 Announce Type: new Abstract: In large-scale recommendation systems like the LinkedIn Feed, content generated by a member's network (connections and follows) makes up over 70% of imp

hardwarearxiv-cs-lg

22 Sept 2026

Connectivity-Aware Exploration of Robotic Grasp Spaces

arXiv:2609.22983v1 Announce Type: cross Abstract: Robotic grasping is typically formulated as the problem of identifying successful actions from a space of candidate grasp poses. However, the organiza

ConsistWorld: Evidence Routing for Consistent Multi-Agent World Models

model-releasesarxiv-cs-cv

arXiv:2609.22641v1 Announce Type: new Abstract: Autoregressive video world models enable temporally coherent generation for a single observer. Extending them to multiple agents requires consistency ac

Constrained Decoding Eliminates Structural Failures in Small LLMs but Reveals a Scale-Dependent Semantic Gap

model-releasesarxiv-cs-cl

arXiv:2609.23742v1 Announce Type: new Abstract: Small open-source large language models (LLMs) in the 0.6B-4B parameter range are increasingly deployed for structured output generation (JSON, function

ContactDP: Contact-Guided Diffusion Policy for Tight Insertion Tasks

arXiv:2609.23800v1 Announce Type: new Abstract: High-precision connector insertion remains challenging for robotic systems due to tight mechanical tolerances, partial observability during contact, and

safetyarxiv-cs-ro

Context Poisoning as Extreme-Value Attention Interference in Long-Context Language Models

arXiv:2609.22101v1 Announce Type: new Abstract: Large language models can process increasingly long prompts, yet their ability to locate and use decisive evidence may degrade as irrelevant or confusab

Contextual Causality with Large Language Models: A Survey

arXiv:2609.22409v1 Announce Type: new Abstract: Understanding contextual causality is critical for large language models (LLMs), as it enables them to accurately identify causal relations in specific

applicationsarxiv-cs-cl

Contrastive Siamese Representation Learning for Predictive Maintenance of Electrical Submersible Pumps

arXiv:2609.22360v1 Announce Type: new Abstract: Electrical submersible pumps (ESPs) are essential in offshore oil production, where unexpected failures can result in significant operational and financ

applicationsarxiv-cs-lg

Local Ai

Contrastive World Models

arXiv:2609.22175v1 Announce Type: cross Abstract: World models trained via pixel reconstruction can struggle in visually complex environments, where irrelevant information dominates the objective and

local-aiarxiv-cs-cv

Contributions to the hierarchy of probabilistic languages

arXiv:2609.23567v1 Announce Type: cross Abstract: We reconsider the theory of probabilistic formal languages generated by n-gram models and by probabilistic context-free grammars (PCFGs). The expected

applicationsarxiv-cs-cl

COREM: Cosine-Relation Momentum Reshaping with Stateful Writeback

arXiv:2609.22487v1 Announce Type: new Abstract: Matrix-valued optimizer states may contain relational structure that is not captured by treating their entries independently. We study whether relations

Correct-by-Construction Vision-based Pose Estimation using Geometric Generative Models

arXiv:2601.17556v2 Announce Type: replace Abstract: We consider the problem of vision-based pose estimation for autonomous systems. While deep neural networks have been successfully used for vision-ba

safetyarxiv-cs-ro

Correct Diagnosis, Better Feedback: A Symbolic-Verifier for Faithful LLM Tutoring Feedback in Logic Proofs

arXiv:2609.22553v1 Announce Type: new Abstract: Effective LLM tutoring depends on correctly identifying the specific error in a student's reasoning before generating feedback. We study this problem in

Correcting Learning-based Perception for Safety

arXiv:2609.22108v1 Announce Type: cross Abstract: Learning-enabled perception is important in many autonomous systems. Unlike traditional sensors, the boundary where ML perception does or does not wor

safetyarxiv-cs-cv

Local Ai

Corrective Forcing: Unified Post-Training for Diffusions and Flows in Generative Speech Enhancement

arXiv:2609.24651v1 Announce Type: new Abstract: Diffusion and flow models, as promising generative paradigms for speech enhancement, face a training--inference mismatch: training uses analytical path

local-aiarxiv-cs-lg

Correlation-Aware Structured Pruning for Large Language Models

arXiv:2609.22131v1 Announce Type: new Abstract: Structured pruning is a promising approach for reducing the substantial inference costs of Large Language Models (LLMs) while maintaining hardware effic

Correlation-Guided Flow Matching with Annealed Masking for Spatial Transcriptomics Generation

arXiv:2609.22187v1 Announce Type: cross Abstract: Spatial transcriptomics (ST) provides spatially resolved gene expression profiling but remains expensive, motivating the prediction of ST from histolo

researcharxiv-cs-cv

Cost-Accuracy Trade-offs: Neural Operator vs Classical Numerical Solver

model-releasesarxiv-cs-lg

arXiv:2609.24021v1 Announce Type: cross Abstract: Neural operators are data-driven models that learn mappings from inputs that parameterize partial differential equations, such as spatially varying co

Cost-Aware Reinforcement Learning with Action Masking and Projection for Battery Energy Storage Dispatch under Suppressed-Spread Market Shifts

arXiv:2609.23590v1 Announce Type: new Abstract: Battery energy storage system (BESS) dispatch must preserve operational feasibility while declining price spreads reduce the margin available to pay for

safetyarxiv-cs-lg

COT-TTS: Audio Context-Aware Text-to-Speech with Chain-of-Thought Reasoning

model-releasesarxiv-cs-cl

arXiv:2609.22697v1 Announce Type: new Abstract: Recently, text-to-speech systems have made significant progress in speech expressiveness and controllability. However, the speaking style of generated s

Counterfactual Tool Ranking under Utility, Cost, and Privilege Constraints

model-releasesarxiv-cs-lg

arXiv:2609.22819v1 Announce Type: new Abstract: Counterfactual tool evaluation must distinguish authority, historical support, and what a comparison actually estimates. We study these distinctions wit

Counting and Covering in Nearest-Neighbour Representations of Boolean Functions

arXiv:2609.23094v1 Announce Type: cross Abstract: We study the number of prototypes needed to represent Boolean functions by nearest-neighbour classification. There are two distinct settings: the prot

Credit Access is Associated with Improved Food Security in the Horn of Africa

arXiv:2609.24382v1 Announce Type: new Abstract: The intensification of climate change poses a growing threat to food security, especially in vulnerable communities. This study employs an observational

Critical-State RL: Diagnosing Trainable States for Multi-Turn Tool Use

arXiv:2609.24985v1 Announce Type: cross Abstract: Multi-turn tool-use failures can hinge on a single model call, yet reward variation alone does not reveal which call would benefit from training. When

safetyarxiv-cs-cl

Cross-Dialect NER for Bangla Regional Dialects Using Leave-One-Dialect-Out Cross-Validation and Explainable AI

model-releasesarxiv-cs-cl

arXiv:2609.22536v1 Announce Type: new Abstract: Bangla, the seventh most spoken language in the world, exhibits significant regional dialectal diversity, with dialects such as Barishal, Chattogram, Sy

CrowdCue: Specialist-Cue Conditioning for Vision-Language Crowd Counting

model-releasesarxiv-cs-cv

arXiv:2609.23012v1 Announce Type: new Abstract: Generative vision-language models (VLMs) offer a counting paradigm in which one model produces both a count and a natural-language account of the scene,

CSC: Calibrated Simplicity for Conflict-Aware Social Bot Detection in the LLM Era

arXiv:2609.23320v1 Announce Type: new Abstract: Social bot detection is essential for protecting online platforms from misinformation amplification, coordinated manipulation, and distorted public disc

Agents

CTRL: Control-Based Time Series Forecasting with LLM-Guided Residual Learning

arXiv:2609.23257v1 Announce Type: cross Abstract: Time series forecasting underpins critical decision-making across diverse domains. While large language models (LLMs) offer promising reasoning capabi

agentsarxiv-cs-cl

CTSpinoPelvic1K: spine, pelvis, ribs and femora in one coordinate frame, annotated for lumbosacral transitional anatomy

arXiv:2609.22760v1 Announce Type: cross Abstract: Purpose: A vertebra at the lumbosacral junction is named by counting caudally from C2 on whole-spine imaging, but a lumbar case is planned on lumbar-o

CultureMINE: Datasets and Methods for Improving the Cultural Capabilities of NLP Systems

arXiv:2609.22494v1 Announce Type: new Abstract: In recent years, there has been a surge of interest in Cultural NLP, with substantial efforts to create globally inclusive NLP systems. The rapid growth

CurvFlow-DTA: dual-graph discrete Ricci curvature flow for drug--target affinity prediction

arXiv:2609.22862v1 Announce Type: new Abstract: Graph neural networks are widely used for drug--target affinity (DTA) prediction, and discrete Ricci curvature has recently been used to characterize mo

Custom Named Entity Recognition and Topic Classification for Global Health Publications

arXiv:2609.24625v1 Announce Type: cross Abstract: How should natural language processing models be selected and adapted for global health literature in environments where annotated data and computatio

CytoCrowd: A Multi-Annotator Benchmark Dataset for Cytology Image Analysis

model-releasesarxiv-cs-cv

arXiv:2602.06674v2 Announce Type: replace Abstract: High-quality annotated datasets are crucial for advancing machine learning in medical image analysis. However, a critical gap exists: most datasets

D-IMPL: A Diffusion-based Solver for Parameterized BBOs

arXiv:2609.22752v1 Announce Type: new Abstract: Diffusion models have demonstrated strong power in generative modeling tasks across multiple domains, exhibiting a remarkable capability of learning com

safetyarxiv-cs-lg

Local Ai

D-JEPA: A Decision-Aligned Latent World Model

arXiv:2609.24749v1 Announce Type: cross Abstract: Latent world models predict the consequences of actions, but accurate prediction does not guarantee that latent distance reflects which candidate will

local-aiarxiv-cs-lg

D3DWA: Adaptive Weight and Prediction-Horizon for Dynamic Window Approach via Dueling Double Deep Q-Network

arXiv:2609.22276v1 Announce Type: new Abstract: The Dynamic Window Approach (DWA) is widely used for local navigation, but its performance depends strongly on parameters that are typically fixed befor

researcharxiv-cs-ro

D3GS: Depth, DINO, and RGB Diffusion Co-Guided 3D Gaussian Splatting for Sparse-View Reconstruction

arXiv:2609.22941v1 Announce Type: new Abstract: Novel view synthesis from sparse inputs remains challenging for 3D Gaussian Splatting (3DGS) due to ambiguous geometry, cross-view inconsistency, and mi

researcharxiv-cs-cv

Agents

Data Agents: Agentic Data Systems

arXiv:2609.24137v1 Announce Type: cross Abstract: Traditional data systems face profound limitations in the AI era, relying on human-crafted pipelines, lacking semantic understanding of heterogeneous

agentsarxiv-cs-cl

'Dear LLaVA, Please Drive': A Depth-Aware Vision-Language Agent for Closed-Loop Robotic Control

model-releasesarxiv-cs-ro

arXiv:2609.22925v1 Announce Type: new Abstract: Vision-language models (VLMs) provide a compelling foundation for reasoning-driven mobile navigation, offering rich contextual understanding and strong

Decentralized Multi-Robot Exploration with Probabilistic Peer Intent and Multi-hop Plan Propagation

arXiv:2609.22726v1 Announce Type: new Abstract: Efficient coordination under limited communication remains a key challenge in decentralized multi-robot exploration. While centralized approaches benefi

applicationsarxiv-cs-ro

DeCo: Efficient Decouple-to-Couple Learning for Multi-Task Visual Grounding

arXiv:2609.24409v1 Announce Type: new Abstract: Multi-task visual grounding requires models to jointly understand linguistic semantics and perform accurate visual localization and segmentation. Despit

researcharxiv-cs-cv

Decomposing Error and Style in Automated Clinical Coding

arXiv:2609.24877v1 Announce Type: new Abstract: In automated clinical coding, where the label space spans tens of thousands of diagnosis and procedure codes, models are currently evaluated against a s

safetyarxiv-cs-cl

Decoupled Causal Discovery

arXiv:2609.23535v1 Announce Type: new Abstract: Causal discovery from observational data is a fundamental yet challenging task in scientific research. While existing approaches are primarily based on

Deep Persona: A Psychologically Grounded Architecture and Evaluation Framework for Role-Playing Agents and Simulations

arXiv:2609.22255v1 Announce Type: new Abstract: Existing approaches to persona simulation with Large Language Models (LLMs) mostly rely on shallow character descriptions that fail to sustain coherent

applicationsarxiv-cs-cl

DeepInstructor: An Agentic AI Instructor for Experience-Driven Idea Evaluation

arXiv:2609.22104v1 Announce Type: new Abstract: As automated scientific discovery advances, Large Language Models (LLMs) can now generate research ideas at an unprecedented scale, shifting the bottlen

safetyarxiv-cs-cl

Defusing Explosive Prompts: Understanding and Preventing Trigger-Based Prompt Injections in LLM Agents

model-releasesarxiv-cs-lg

arXiv:2609.22510v1 Announce Type: cross Abstract: As LLM applications integrate with external tools, they are increasingly exposed to indirect prompt injection (IPI), where adversarial instructions ar

Tutorials

Dense-Prior-Guided Generative Video Compression

arXiv:2604.06655v2 Announce Type: replace Abstract: Diffusion-based generative video compression offers a promising paradigm for low-bitrate reconstruction, but existing keyframe-based controllable ap

tutorialsarxiv-cs-cv