Search: “context”

Engrams Embedding Entendre: Codesign for Efficient DRAM/SSD Offloading

model-releasessemianalysis

Engram Embedding Entendre is a model‑architecture optimization that extends standard token embeddings with learned multi‑token lookups, enabling recurring local patterns to be retrieved directly from

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Safety

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

DGX agent

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

18 Sept 2026

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

How competitive are journals compared to top ai conferences? [D]

researchr-machinelearning

Hi everyone, The NeurIPS results aren’t out yet, but I’m expecting my paper to be rejected, so I’m considering submitting it to a journal instead. My scores were 2/3/3 (3/4/4). I feel like I would pro

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

inclusionAI/Realtime-Venus · Hugging Face

do you want some omni? here is omni for you 1. 🧭 Overview This repository hosts two checkpoints of the Realtime-Venus system: Realtime-Venus-Omni (Realtime-Venus-Omni/): the 9B audio-visual interactio

local-air-localllama

Introducing the first in our Parsed by LlamaParse series. We're outlining the stakes of 'getting parsing wrong' in consequential documents. …

Introducing the first in our Parsed by LlamaParse series. We're outlining the stakes of 'getting parsing wrong' in consequential documents. We’re starting with the U.S. Energy Information Administrati

agentsllamaindex--x

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

🚀 Meet Qwen3.8-Omni-Flash, Qwen's first omni-modal model built around agentic capabilities! Native audio-video understanding, reasoning, an…

🚀 Meet Qwen3.8-Omni-Flash, Qwen's first omni-modal model built around agentic capabilities! Native audio-video understanding, reasoning, and tool use come together in one model: understand the content

model-releasesqwen--x

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

My long ChatGPT threads quietly forget the beginning, so I keep decisions somewhere else

Been working on this backend migration for like two weeks and my chat with ChatGPT is one of those endless scrolls. Last Tuesday it confidently told me we'd 'decided' on the wrong database. We had lit

model-releasesr-chatgpt

Ollama vs. LM Studio vs. ?

Hi everyone, I’ve been experimenting with local LLMs on my 48 GB RAM MacBook Pro and I’m still trying to figure out what the best setup is. Ollama feels very fast, which I really like. The problem for

model-releasesr-ollama

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

model-releasesarxiv-cs-cl

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

Question: UkisAI Swift Ternary Bonsai 2 27B?

model-releasesr-localllama

Hey community, Jovan from UkisAI here, We're the team behind Swift Qwen3.8 27B, the Qwen model with token usage and overthinking error improvements Our estimate is that we can make a great improvement

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

model-releasesarxiv-cs-cl

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