Search: “retrieval”

arXiv:2609.39392v1 Announce Type: new Abstract: Autonomous research agents can generate hypotheses and conduct experiments, but experimentation remains a major source of computational cost. A fundamen

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Explore-on-Graph: Hybrid Embedding-LLM Reasoning for Knowledge Graph Question Answering under Incompleteness

DGX agent

arXiv:2609.39786v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly combined with knowledge graphs (KGs) to ground reasoning in structured evidence. However, most LLM-based K

model-releasesarxiv-cs-cl

1 Oct 2026

Local Ai

Five roles for an Ollama-based workflow: architecture walkthrough + Python scaffold

Hi everyone — I'm behind Autonomous Workday, and I'm sharing an English-language architecture walkthrough about building an event-driven workflow around local inference. The proposed flow separates fi

local-air-ollama

Forging LLM Authorship Fingerprints with Targeted Rewriting

arXiv:2609.38831v1 Announce Type: new Abstract: Model-attribution classifiers can often identify which language model produced a text, making model-specific writing patterns a signal of provenance. Ac

researcharxiv-cs-cl

Applications

From Tweets to Trades: Analyzing the Influence of Public Mood over Stock Market Performance in Turkiye

arXiv:2609.40064v1 Announce Type: new Abstract: Purpose: This study examines whether domain-specific public mood is associated with stock-market dynamics and whether these relationships vary across co

applicationsarxiv-cs-cl

Front-to-Back: Benchmarking Vision-Language Models for Asymmetric Cross-View Vehicle Re-Identification

arXiv:2609.39492v1 Announce Type: new Abstract: Matching the same vehicle across front and rear cameras is difficult because the cameras do not share a view and the vehicle's appearance changes substa

Grounding Time-Series Foundation Models in Digital Twin Topology for Predictive Maintenance

arXiv:2609.40071v1 Announce Type: cross Abstract: Digital twins increasingly support downstream analytical tasks that depend on time-series data, motivating interest in time-series foundation models (

Hermes: Learning Contextual Reasoning Unlocks Test-Time Scaling

arXiv:2609.38332v1 Announce Type: cross Abstract: Test-time scaling improves model performance by allocating additional compute during inference. Using this compute effectively across multiple context

tutorialsarxiv-cs-ai

Index-Translate: A Multilingual Translation Model Family -- Text, Speech, Controlled Dubbing, and Long-Document Translation

model-releasesarxiv-cs-cl

arXiv:2609.40181v1 Announce Type: new Abstract: We introduce Index-Translate, a multilingual translation model family that combines a shared multilingual foundation with specialized training for gener

Linguistic Loopholes in LLM Unlearning: From a 174-Language Benchmark to Coverage-Aware Unlearning

arXiv:2609.40286v1 Announce Type: cross Abstract: Unlearning a fact in one language does not guarantee its removal in others as changing the query or even the requested answer language can reopen seem

Hardware

MEMO: Multi-Level Entity-Aware Memory for Streaming Video Understanding

arXiv:2609.38900v1 Announce Type: new Abstract: Streaming video understanding requires models to process unbounded visual streams while preserving rich visual semantics across vast temporal horizons,

hardwarearxiv-cs-cv

NMIXX: Domain-Adapted Neural Embeddings for Cross-Lingual eXploration of Finance

arXiv:2507.09601v3 Announce Type: replace-cross Abstract: Financial text embeddings must distinguish changes in event status, perspective, and obligations even when passages share similar wording. NMI

Online Evolution Strategy for Flow-Matching VLA Policies via Self-Supervised Trajectory Distribution Optimization

arXiv:2609.38855v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models based on generative frameworks, such as Flow Matching, have recently achieved impressive performance in robotic ma

Overview of BioASQ 2026: The fourteenth BioASQ Challenge on Large-Scale Biomedical Semantic Indexing and Question Answering

arXiv:2609.39975v1 Announce Type: cross Abstract: This paper presents an overview of the fourteenth edition of the BioASQ challenge, organized in the context of the Conference and Labs of the Evaluati

PANDA: A Decentralized Architecture with Flexible Orchestration for Scalable, Fault-Tolerant Multi-Agent Systems

arXiv:2609.38482v1 Announce Type: cross Abstract: Existing architectures for LLM-based multi-agent systems (MAS) cannot reliably and efficiently solve multi-step tasks at scale: they struggle to suppo

Policy-Conditioned AI-Use Detection: An Evidentiary Framework for Academic Publishing

arXiv:2609.38427v1 Announce Type: cross Abstract: Major venues now publish detailed rules about how authors, reviewers, and area chairs may use AI, and those rules differ by role, by task, and by what

safetyarxiv-cs-ai

Agents

RefCon: Iterative Refinement and Contrastive Memory Extraction for Context-Evolving Agent

arXiv:2609.39143v1 Announce Type: new Abstract: Long-horizon agent interactions generate useful but noisy experience, and retraining models to absorb it is expensive. Context-evolving agents therefore

agentsarxiv-cs-ai

Representation Risk in Pretrained Image Encoders

arXiv:2609.35470v1 Announce Type: cross Abstract: Applied researchers increasingly convert images into features with pretrained encoders, then use those features in a downstream prediction model. The

Agents

SkillFM: Generating Skills for LLM Agents via Latent Flow Matching

arXiv:2609.39382v1 Announce Type: new Abstract: Textual skills provide reusable guidance for large language model agents, but existing approaches often rely on manually curated skill banks or reinforc

agentsarxiv-cs-ai

Synthetic Pre-pretraining Survives Scale, but Not as a Grammatical Prior

arXiv:2609.39827v1 Announce Type: cross Abstract: Pre-pretraining (PPT) on synthetic non-natural language data improves token efficiency during language model pre-training (PT). Prior work attributes

TALK-Dem: Benchmarking Embodied Task Planning under Dementia-Associated Communication Patterns

model-releasesarxiv-cs-cl

arXiv:2609.38371v1 Announce Type: cross Abstract: Existing LLM-driven robot task planners rely on a taken-for-granted assumption of an ideal user whose instructions are clear, complete, and task-focus

AdaptArena: Evaluating Test-Time Personalization of Web Agents

model-releasesarxiv-cs-lg

arXiv:2609.36488v1 Announce Type: new Abstract: Large language model (LLM) agents have demonstrated strong performance on complex web navigation tasks, yet they remain brittle in real-world settings w

Asking for What Was Never Requested: Horizontal and Vertical Proactivity in Agents

arXiv:2609.37236v1 Announce Type: new Abstract: An agent that uses tools typically responds to what the user explicitly asks, yet completing the task may require information the user never requested.

Audience-Bound Persistent Memory: Authorization Across the Memory Lifecycle

arXiv:2609.36373v1 Announce Type: cross Abstract: A personal language agent that acts for its owner across private and shared conversations can learn a fact from one audience and later place it in the

safetyarxiv-cs-ai

CredWise: A Controlled Agentic Decision-Intelligence Framework for Explainable and Auditable Credit-Risk Assessment

model-releasesarxiv-cs-cl

arXiv:2609.37223v1 Announce Type: new Abstract: Credit-risk prediction is important in banking, but a prediction alone does not explain why an applicant is risky or how it should be combined with othe

Divide and Inject: Can Agents Reconstruct an Indirect Prompt Injection from Fragments?

arXiv:2609.36576v1 Announce Type: new Abstract: Agentic systems are now being widely used to orchestrate tools and reason over long contexts. However, the improving capabilities of the large language

safetyarxiv-cs-ai

Local Ai

FM-ReID: Selective Competitive Token Routing for Object Re-Identification

arXiv:2609.36560v1 Announce Type: cross Abstract: Object re-identification (ReID) faces a recurring challenge: different identities can share highly similar global appearances, while the cues that dis

local-aiarxiv-cs-ai

In-Context Learning Amplifies a Latent Symbolic Circuit

arXiv:2609.36265v1 Announce Type: cross Abstract: Large language models can learn abstract rules from just a few in-context examples, but how their internal mechanisms activate as examples accumulate

tutorialsarxiv-cs-ai

Mara Chain: Rethinking Failure as a Stepping Stone for AI System Auto-Evolution

arXiv:2609.35855v1 Announce Type: cross Abstract: Optimizing deployed AI systems increasingly amounts to editing prompts, skills, harnesses, and code rather than model weights. Existing approaches com

MemEvo: Automatic Discovery of Streaming Video Memory Mechanisms

arXiv:2609.36581v1 Announce Type: new Abstract: Query-agnostic streaming video understanding requires vision-language models to continuously compress an indefinitely growing visual stream into a bound

tutorialsarxiv-cs-ai

RareDx: Controlled Knowledge Integration and Graph-Grounded Policy Optimization for Rare-Disease Diagnosis

arXiv:2609.35549v2 Announce Type: replace Abstract: Rare-disease diagnosis is a long-tail reasoning problem: phenotypes are incomplete, individual disorders are sparsely documented, and relevant evide

RoboHarn-Evo: Evolving Hierarchical Physical Knowledge for Self-Improving Robotic Manipulation

model-releasesarxiv-cs-ro

arXiv:2609.37583v1 Announce Type: new Abstract: Vision-language models can coordinate long-horizon robot manipulation, yet successful task reasoning still depends on whether local physical interaction

Seeing Is Not Addressing: Auditing Linguistic Access to Frozen Visual Geometry

arXiv:2609.37230v1 Announce Type: new Abstract: Visual distinctions are often finer than those reflected in linguistic conceptualization. Vision-language models exhibit a similar asymmetry: a distinct

safetyarxiv-cs-cv

Simple Agentic Memory for Generalist Robot Policies

arXiv:2609.36595v1 Announce Type: cross Abstract: Visual-memory systems commonly retain or compress past observations. Robot control additionally requires interaction-derived state that no individual

V-Engram: Trigger-Indexed External Memory for Modular Text-to-Image Personalization

arXiv:2609.37198v1 Announce Type: new Abstract: Pretrained text-to-image models contain broad visual knowledge, yet they cannot reliably acquire or refine a specific visual identity from only a few re

Amnesia by Design, Memory By Necessity: Persistent State for Document Intelligence

arXiv:2609.32041v1 Announce Type: new Abstract: Modern Document AI reads contracts, extracts fields, reasons over tables, and grounds answers to page regions, then forgets everything. Processing an am

Beyond Token Scale: Chunk-Level Sparse Autoencoders for Reliable Semantic Feature Discovery

arXiv:2609.35521v1 Announce Type: cross Abstract: Sparse autoencoders (SAEs) expose features that help us understand and steer language models, but faithful reconstruction does not guarantee informati

researcharxiv-cs-lg

Distance-KV: Exploiting Relative Distance for Efficient Long-Context Inference

model-releasesarxiv-cs-lg

arXiv:2609.32663v1 Announce Type: new Abstract: The memory usage and decoding latency of LLM inference grow rapidly with context length. To reduce these costs, key-value (KV) cache compression methods

Memory in the Sky: Low-Altitude Question Answering with Multi-Agent Memory Aggregation

model-releasesarxiv-cs-ro

arXiv:2609.35431v1 Announce Type: new Abstract: This paper studies low-altitude question answering (LAQA), in which distributed unmanned aerial vehicle (UAV) memories are aggregated at a ground server

mmHRI: Towards Privacy-Preserving Human-Robot Interaction with Millimeter-Wave Radar

arXiv:2609.34220v1 Announce Type: cross Abstract: Assistive robots increasingly operate in many human-centered environments and perform various human-robot interaction (HRI) tasks, such as object deli

safetyarxiv-cs-cv

PlaylistEval: Can Video-Language Judges Be Trusted at Day Scale and Beyond?

arXiv:2609.34314v1 Announce Type: new Abstract: Video-language models are increasingly used as judges of video understanding, both for evaluating model outputs and for training reward models. Whether

QiYao-M: Multimodal Time Series Foundation Model with Role-Aware Modeling of Endogenous and Exogenous Modalities

arXiv:2609.34842v1 Announce Type: new Abstract: Existing multimodal time series foundation models (TSFMs) typically model heterogeneous modalities through largely shared mechanisms, overlooking the di

tutorialsarxiv-cs-lg

Relevance Does Not Imply Applicability: Experience Activation for Personal GUI Agents

arXiv:2609.33304v1 Announce Type: new Abstract: Personal Graphical User Interface (GUI) agents rely on interaction history to infer what a user wants from ambiguous instructions and to anticipate recu

safetyarxiv-cs-cv

Local Ai

Structured Residual Connectivity Matters for Diffusion Transformers

arXiv:2609.33203v1 Announce Type: new Abstract: Diffusion Transformers (DiTs) have established themselves as a scalable backbone for high-fidelity image synthesis. However, unlike U-Net based diffusio

local-aiarxiv-cs-cv

Applications

When Less Compute Is More: Adaptive Early Exit Improves Pretrained Outlier Detection

arXiv:2609.32898v1 Announce Type: new Abstract: Pretrained tabular foundation models process every dataset at a fixed depth, with inference costs growing with dataset size. To address this, we present

applicationsarxiv-cs-lg

A Benchmark and Diagnostic Study of Epistemic Admission in Shared Agent Memory

arXiv:2609.30813v1 Announce Type: new Abstract: Evaluating claim admission in shared agent memory is challenging because repeated claims may be mistaken for independent evidence. An agent may copy or

28 Sept 2026

'AI is (not) the new...': A Diagnostic Analogy Framework for Generative AI's Cultural Impacts

arXiv:2609.31482v1 Announce Type: new Abstract: Generative AI is reshaping the cultural infrastructures through which knowledge is found, synthesized, and held accountable. To make sense of this shift

28 Sept 2026

Aurora-X: Built for Extreme Time Series Forecasting