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Benchmarking LLM Compliance with China AI Generated Content Regulations

arXiv:2609.19989v1 Announce Type: new Abstract: The widespread adoption of LLMs has led to escalating content compliance risks. Prior works have contributed to addressing these risks in the English co

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Chunk Twice, Embed Once: A Systematic Study of Segmentation and Representation Trade-offs in Chemistry-Aware Retrieval-Augmented Generation

DGX agent

arXiv:2506.17277v2 Announce Type: replace-cross Abstract: The retrieval stage of retrieval-augmented generation (RAG) for scientific question answering depends on how documents are segmented and how c

model-releasesarxiv-cs-ai

18 Sept 2026

Closed-World Resolution Against Tool Hallucination in LLM Agents

arXiv:2609.19425v1 Announce Type: new Abstract: Tool-augmented large language model (LLM) agents fail in a way no tool-selection or tool-security method addresses: they call tools that do not exist an

Don't Mask the Environment: Observation Supervision Changes How Agents Explore Under RL

arXiv:2609.20715v1 Announce Type: cross Abstract: Agent trajectories record what an agent does and what happens next. Yet standard supervised fine-tuning (SFT) applies loss only to agent-authored acti

safetyarxiv-cs-ai

EconSkills: Studying Skill Transfer and Retrieval for Web Agents on Live Economic Data

arXiv:2609.19523v1 Announce Type: new Abstract: Web agents often revisit the same sites, yet most evaluations discard the procedures learned in earlier successful interactions. We introduce EconSkills

agentsarxiv-cs-ai

Enhancing the Perception of Safety and Comfort during Physical Human-Robot Handshake Interactions by Integrating Flexible Elements into a Robotic Arm

arXiv:2609.19375v1 Announce Type: new Abstract: Safety and comfort in human-robot physical in-teractions are essential aspects in the development of social technologies, where natural gestures, such a

safetyarxiv-cs-ro

FacetCRS: Multi-Faceted Preference Learning for Pricking Filter Bubbles in Conversational Recommender System

arXiv:2609.20175v1 Announce Type: cross Abstract: The filter bubble is a notorious issue in Recommender Systems (RSs), which describes the phenomenon whereby users are exposed to a limited and narrow

Factors Influencing the Emergence of Dependency Length Minimization in Neural Agent Simulations

arXiv:2609.06025v2 Announce Type: replace Abstract: Given various grammatical options, language users prefer the word order choice that reduces the overall length of syntactic dependencies, a principl

agentsarxiv-cs-cl

Full-Duplex Speech Models Take the Floor When Asked, Not When Needed

arXiv:2609.19596v1 Announce Type: new Abstract: Full-duplex speech models listen and speak at once, promising always-on assistants. Yet they must also decide when they should speak. Human listeners sp

researcharxiv-cs-cl

GPT-6-Astra in a Navigation Workflow: Behavioral Analysis in Zero-Shot Vision-and-Language Navigation in Continuous Environments

arXiv:2609.20116v1 Announce Type: new Abstract: We study GPT-6-Astra in a zero-shot Vision-and-Language Navigation in Continuous Environments (VLN-CE) system, where it interprets instructions, assesse

agentsarxiv-cs-ro

HOPHY: A Hierarchical Hypergraph Representation for Off-Road Path and Mission Planning

arXiv:2609.20694v1 Announce Type: new Abstract: Mission-level autonomy for disaster response, search and rescue, and tactical UGV operations requires repeated path and mission planning as terrain cond

agentsarxiv-cs-ro

IMFD: End-to-end Multi-Face Forgery Detection through Instruction-based Large Vision-Language Models

arXiv:2609.19693v1 Announce Type: new Abstract: The rapid increase of deepfakes has raised significant concerns due to their spread on social media. Traditional multi-face forgery detectors crop and v

researcharxiv-cs-cv

Is It Still Worth Training a Classical Model in the Era of LLMs? A Crossover Benchmark on Tabular Data

arXiv:2609.20218v1 Announce Type: cross Abstract: Large language models can label a tabular row from a plain-English description with no training - a capability now shipping in mainstream spreadsheet

JEPA-WAM: Connecting Generated Visual Instructions to World Action Models through JEPA Latent Representations

arXiv:2609.20277v1 Announce Type: new Abstract: World Action Models (WAMs) have demonstrated strong robotic manipulation capabilities by augmenting pretrained video generative models with action exper

Tutorials

Learn Your Own Thoughts: Abstract Token Curriculum

arXiv:2609.19717v1 Announce Type: cross Abstract: Large Language Models (LLMs) have achieved remarkable reasoning capabilities by utilizing chain-of-thought (CoT) as a scratchpad for intermediate stag

tutorialsarxiv-cs-ai

Lens: Bringing the Right Semantic Perspective into Focus for Training-Free Multimodal Representation Learning

arXiv:2609.20252v1 Announce Type: cross Abstract: High-quality representations are essential for a wide range of downstream tasks. Dedicated embedding models are explicitly optimized for representatio

Applications

LMEnt: A Suite for Analyzing Knowledge in Language Models from Pretraining Data to Representations

arXiv:2509.03405v2 Announce Type: replace Abstract: Language models (LMs) increasingly drive real-world applications that require world knowledge. However, the internal processes through which models

applicationsarxiv-cs-cl

MeshKV: A Network-on-Chip KV Cache Fabric for Scalable Transformer Decoding Accelerators

arXiv:2609.19207v1 Announce Type: cross Abstract: Autoregressive transformer decoding is constrained by irregular key-value (KV) cache movement on tiled accelerators. Prior compression and DRAM-placem

MM-Future: Multi-Mode Joint World-Action Modeling for Autonomous Driving

arXiv:2609.20377v1 Announce Type: new Abstract: Autonomous driving involves coupled decision-making and scene evolution under multi-mode uncertainty. To capture this coupling and uncertainty, we intro

agentsarxiv-cs-cv

MTF-Net: Multi-Modal Temporal Feature Fusion Network for Pedestrian Intention Prediction

arXiv:2609.20178v1 Announce Type: new Abstract: Accurately predicting pedestrian intentions is crucial for ensuring safe and proactive interaction between autonomous vehicles and pedestrians. However,

local-aiarxiv-cs-cv

Online Adaptation of Visual Odometry Frontends with Image-Conditioned Reinforcement Learning

model-releasesarxiv-cs-cv

arXiv:2603.21785v2 Announce Type: replace Abstract: Visual odometry (VO) frontends are typically tuned offline by domain experts on pre-recorded datasets and then deployed with fixed hyperparameters.

Tutorials

Parallelism, critical windows, and separations among diffusion language models

arXiv:2609.20539v1 Announce Type: new Abstract: A popular selling point of diffusion large language models (dLLMs) is their capacity for parallelism: the ability to generate sequences of text far more

tutorialsarxiv-cs-lg

PerSeM: Persistent Semantic Memory for Long-Horizon Open-Vocabulary UAV Mapping

arXiv:2609.19542v1 Announce Type: new Abstract: Open-vocabulary segmentation enables rich semantic perception for UAVs, but frame-wise predictions can remain temporally inconsistent across repeated ob

researcharxiv-cs-cv

PersonalAI 2.0: Enhancing knowledge graph traversal/retrieval with planning mechanism for Personalized LLM Agents

arXiv:2605.13481v2 Announce Type: replace Abstract: We introduce PersonalAI 2.0 (PAI-2), a novel framework designed to enhance LLM-based systems through integration of external knowledge graphs (KGs).

PointEvent: Rethinking Event-based Tiny Object Detection via Serialized Motion Evidence Accumulation

arXiv:2609.20066v1 Announce Type: cross Abstract: Event cameras offer high temporal resolution and motion sensitivity for tiny UAV detection, yet distant targets generate sparse and fragmented events

local-aiarxiv-cs-ai

Q&A on Any Spreadsheet Requires Interpreting Its Grid Structure

arXiv:2609.20732v1 Announce Type: new Abstract: Semantic cell annotation improves chunking interpretability for spreadsheets in LLM-driven RAG systems, aiding answer generation through enriched contex

Quantifying Overclaiming Propensity in Frontier LLM Agents

arXiv:2609.20812v1 Announce Type: cross Abstract: Frontier coding agents are increasingly trusted to work autonomously for long periods, yet an agent's final response is often the only account of that

agentsarxiv-cs-ai

Recursive Quantum Long Short-Term Memory for Stable Short-Horizon Temperature Forecasting

arXiv:2609.20594v1 Announce Type: new Abstract: Quantum long short-term memory (QLSTM) models extend recurrent sequence learning with variational quantum circuits, but their optimization behavior can

researcharxiv-cs-lg

Red-Teaming Auto Mode: Improving Blocking Classifiers Against Malign Coding Agents

arXiv:2609.19587v1 Announce Type: cross Abstract: To keep coding agents from going off the rails, production systems now review each proposed action with a blocking monitor that can reject it before i

Redact or Keep? A Fully Local AI Cascade for Educational Dialogue De-Identification

arXiv:2606.18372v2 Announce Type: replace-cross Abstract: Educational dialogue is a valuable but sensitive resource for research: the same transcripts that capture authentic learning often capture per

local-aiarxiv-cs-ai

Reproducibility is not construct validity: LLM measurement of institutionally situated communication

arXiv:2609.19866v1 Announce Type: new Abstract: High annotation reproducibility does not necessarily imply that an LLM-inferred measure captures the construct it is intended to measure. We test this d

safetyarxiv-cs-ai

Reproducing Transparent and Scrutable Recommendations: Exploring Open-Weight Models via Natural-Language User Profiles

arXiv:2609.19831v1 Announce Type: cross Abstract: In this reproducibility study, we investigate the transparency and scrutability of recommender systems enhanced by incorporating generated natural-lan

ReShoot: Generative Visual Domain Randomization of Recorded Robot Demonstrations for Visuomotor Policy Learning

arXiv:2609.19661v1 Announce Type: new Abstract: Imitation-learned robot policies are frequently overfit to the visual conditions present in their training demonstrations. Consequently, variations in o

safetyarxiv-cs-ro

SAFARI: An Industrial Benchmark for LLM-Assisted Hazard Analysis and Risk Assessment

arXiv:2609.20584v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly considered for safety-critical engineering, yet their reliability in regulated functional-safety workflows

Scene-Conditioned Relation Routing for urban cellular activity forecasting

arXiv:2609.20209v1 Announce Type: cross Abstract: Urban cellular activity forecasting requires jointly modeling heterogeneous spatiotemporal signals, including SMS usage, mobile network traffic, and c

Applications

Scene-Q: Confidence-Aware Coarse-to-Fine Querying of 3D Scenes with Selective VLM Reasoning

arXiv:2609.20235v1 Announce Type: new Abstract: Indoor mobile robots require open-vocabulary scene understanding that grounds natural-language queries in a consistent 3D map. Many existing systems ult

applicationsarxiv-cs-cv

SnapPhysics: A Physics-Aware Scene Graph from a Single View for Interactive Mixed Reality Scenes

model-releasesarxiv-cs-cv

arXiv:2609.19815v1 Announce Type: new Abstract: We propose SnapPhysics, a training-free framework that reconstructs 3D objects and estimates their physical properties such as mass, friction, and cente

SoL-Pi: Recursively Scaling Auto-Research Loops for Efficient Agent Harness

arXiv:2609.20519v1 Announce Type: new Abstract: As coding agents move from supervised code completion to unattended, around-the-clock exploration, their work expands from isolated predictions into lon

State-Change Learning for Prediction of Future Events in Endoscopic Videos

arXiv:2510.12904v2 Announce Type: replace Abstract: Surgical future prediction, driven by real-time AI analysis of surgical video, is critical for operating room safety and efficiency. It provides act

safetyarxiv-cs-cv

Structured Four-Stage Legal Translation: From Natural-Language Traffic Rules to PROLOG

arXiv:2609.20334v1 Announce Type: new Abstract: Traffic regulations are written for human interpretation and therefore rely on shared background knowledge and flexible phrasing, which inherently intro

The AR Fairness Metamodel: A Structured Framework for Fairness Measures

arXiv:2609.19234v1 Announce Type: cross Abstract: This paper presents the AR fairness metamodel, a framework designed to represent, analyze, and compare different fairness scenarios. The metamodel con

safetyarxiv-cs-ai

TorchCraft: Unified binder design by inverting an all-atom structure predictor

arXiv:2609.19770v1 Announce Type: new Abstract: All-atom structure predictors model diverse molecular interactions, but using their learned structural priors for binder design remains challenging. Her

TRACE: Accountable Agentic Retrieval for Source Discovery in Digital Archives

arXiv:2609.19897v1 Announce Type: new Abstract: Historical archives pose a difficult retrieval problem for retrievalaugmented generation systems: documents are OCR-degraded, heterogeneous across genre

VABench: Measuring Embodied Spatial Intelligence through Visual Demonstrations, Active Perception, and Metric Control

arXiv:2609.19554v1 Announce Type: cross Abstract: Spatial intelligence requires more than describing object locations. Under incomplete observation, models must identify and acquire missing evidence,

local-aiarxiv-cs-cv

Video DeltaNet: A Video-Native Hybrid Attention for Livestream Video Generation

arXiv:2609.20744v1 Announce Type: new Abstract: Video diffusion models repeatedly process long spatiotemporal token sequences during denoising, making attention a major computational bottleneck. Linea

safetyarxiv-cs-lg

When Perplexity Lies: Generation-Focused Distillation of Hybrid Sequence Models

arXiv:2603.26556v3 Announce Type: replace-cross Abstract: Converting a pretrained Transformer into a more efficient hybrid model through distillation offers a promising approach to reducing inference

A Benchmark Suite and Ground-Truth Methodology for Formal Verification of IEC 61131-3 Ladder Diagram Programs

arXiv:2609.18994v1 Announce Type: new Abstract: We present the first benchmark suite for formal verification of Programmable Logic Controller (PLC) programs that combines controlled ground truth with

17 Sept 2026

A Calibrated Instrument for Measuring How Inference Optimizations Affect Output Quality

arXiv:2609.18005v1 Announce Type: new Abstract: Large language model optimization is an active research area, spanning quantization of model weights, early-exit methods for skipping layers, and specul