Search: “context”

Measuring Pragmatic Influence in Large Language Model Instructions

arXiv:2602.21223v2 Announce Type: replace Abstract: It is not only what we ask large language models (LLMs) to do that matters, but also how we ask them. Phrases like ``This is urgent'' or ``As your s

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MedSNIP: Building and Benchmarking Snippet-Level Granularity for Medical Fact Verification

DGX agent

arXiv:2609.12884v1 Announce Type: new Abstract: A medical claim's correctness often depends not on the claim alone, but on the clinical structure around it. A claim may require a lab reference range,

model-releasesarxiv-cs-cl

14 Sept 2026

MoPA: Coordinated Mobile Manipulation via Subsystem-Specific Perception Alignment

model-releasesarxiv-cs-cv

arXiv:2609.12081v1 Announce Type: cross Abstract: Mobile manipulation requires perceptual evidence at different spatial scales for base motion and arm control, while the two action modalities remain k

Not All Speech Is Intent: Adaptive Self-Correcting Inference Layer for Post-ASR False Wake-Up

model-releasesarxiv-cs-cl

arXiv:2609.12469v1 Announce Type: new Abstract: False wake-up activations remain a persistent challenge in conversational AI. Speech phonetically similar to a device's wake word can produce a syntacti

Optimizing for the decision not the prediction: an exploration of Smooth Net Benefit as a training objective

model-releasesarxiv-cs-lg

arXiv:2609.12752v1 Announce Type: new Abstract: Objective Prediction models are commonly trained using objectives such as Bernoulli negative log-likelihood (NLL), although downstream clinical decision

PACIFIC: Can LLMs Discern the Psychometric Traits Influencing Your Preferences? Personality-Driven Preference Alignment in LLMs

arXiv:2602.07181v4 Announce Type: replace Abstract: User preferences are increasingly used to personalize Large Language Model (LLM) responses, yet reliably leveraging preference signals remains under

safetyarxiv-cs-cl

Parameter-Efficient Retrievers for Polish and European Languages

model-releasesarxiv-cs-cl

arXiv:2609.12913v1 Announce Type: new Abstract: Dense retrieval systems increasingly rely on multi-billion-parameter language models, whose memory and computational requirements make large-scale index

Partition-Invariant Tuning for 3D Scene Understanding

model-releasesarxiv-cs-cv

arXiv:2609.12473v1 Announce Type: new Abstract: Scene-level point cloud understanding remains challenging due to diverse geometries and spatial layouts. While pre-trained 3D point cloud foundation mod

Pelican-Sim 1.0: A General World Model Simulator for Embodied Intelligence

arXiv:2609.12036v1 Announce Type: new Abstract: In this technical report, we propose Pelican-Sim 1.0, a general world model simulator for embodied intelligence that predicts future observations from v

safetyarxiv-cs-ro

Prism-SQA: An Interpretable and Adaptable Neural Framework for Surface Electromyography Quality Assessment

arXiv:2609.12724v1 Announce Type: cross Abstract: sEMG is vulnerable to various contaminants that distort signal morphology and spectral content. Accurate signal quality assessment (SQA) is essential

researcharxiv-cs-lg

READ: Learning Risk-Informed Fields for End-to-End Autonomous Driving

arXiv:2609.12371v1 Announce Type: new Abstract: Autonomous driving requires more than recognizing what is present in a scene: a planner must determine how road structure, surrounding agents, and their

safetyarxiv-cs-ro

RunningTensor: Generalizing Linear Attention to Higher-Order Recurrent States

arXiv:2609.12814v1 Announce Type: new Abstract: Linear attention and state-space models provide linear-time sequence modeling, but their recurrent memory remains a second-order tensor (a matrix), limi

researcharxiv-cs-lg

Same Encoder, Different Winner: A Paired-View Framework for Cell Painting Encoder Evaluation

arXiv:2609.12761v1 Announce Type: new Abstract: Vision encoders for Cell Painting are typically ranked by a single evaluation, commonly replicate mean average precision (mAP). We introduce CP-BG-Bench

researcharxiv-cs-cv

Space as an Interventional Invariant: Cross-Modal Predictive Geometry for Stratified Cities and Em-Spaced Intelligence

arXiv:2609.11959v1 Announce Type: cross Abstract: Space is a foundational concept across mathematics, physics, spatial cognition, urban science, and embodied intelligence, yet these fields often treat

local-aiarxiv-cs-cl

Synthetic Blips: Generalizing Synthetic Controls for Dynamic Treatment Effects

arXiv:2210.11003v3 Announce Type: replace-cross Abstract: We propose a generalization of the synthetic control methods to the setting with dynamic treatment effects, in which each unit receives multip

safetyarxiv-cs-lg

Applications

SynthSentry: Detecting Synthetic Data Contamination in Language Model Training Data

arXiv:2609.12353v1 Announce Type: new Abstract: Large language models trained recursively on their own or other models' outputs undergo model collapse, in which distributional tails and factual accura

applicationsarxiv-cs-cl

The Battery Price of edge AI: A study of the Environmental Impact of LLM Inference on Mobile Devices

arXiv:2609.11940v1 Announce Type: cross Abstract: The rapid diffusion of generative artificial intelligence raises privacy, latency, and performance concerns that motivate a shift toward 'local-first'

local-aiarxiv-cs-lg

The Cost of Compression: A Rate-Distortion Limit on Factual Hallucination

arXiv:2609.12111v1 Announce Type: new Abstract: Factual hallucination in closed-book question answering is often treated as a coverage problem: a model fails because the relevant fact is absent from i

Tutorials

Transfer Learning for Evolving Domains

arXiv:2609.13039v1 Announce Type: new Abstract: Transfer learning explores how to leverage knowledge from various tasks or domains (sources) to enhance predictive performance in related tasks or domai

tutorialsarxiv-cs-lg

UniMo: Unifying Human and Animal Motion Generation

arXiv:2609.12342v1 Announce Type: new Abstract: The conditional generation of 3D motion has emerged as a key research topic due to its wide applicability across robotics, AR/VR, gaming, and content cr

researcharxiv-cs-cv

When Bias Pretends to Be Truth: How Spurious Correlations Undermine Hallucination Detection in LLMs

model-releasesarxiv-cs-cl

arXiv:2511.07318v3 Announce Type: replace Abstract: Despite substantial advances, large language models (LLMs) continue to exhibit hallucinations, generating plausible yet incorrect responses. In this

When Ground-Truth Fidelity Matters: An Orchestrated UAS Framework for Wheat Streak Mosaic Virus Detection Using Vision Transformers and Machine Learning

arXiv:2609.12169v1 Announce Type: new Abstract: Wheat streak mosaic virus (WSMV) is a destructive pathogen of sweet corn and other cereal crops, causing yield losses and complicating early detection b

safetyarxiv-cs-cv

When2Talk: When Should a Proactive In-Car Agent Talk?

arXiv:2609.12503v1 Announce Type: cross Abstract: Proactive in-cabin agents can help passengers understand automated-vehicle (AV) behavior, but communicating every ride event may introduce unnecessary

safetyarxiv-cs-cv

An AI-Powered Culturally Aware Chatbot for Stress Detection and Wellness Support among Pakistani University Students Using NLP and Machine Learning

arXiv:2609.11199v1 Announce Type: new Abstract: With the existing digital mental health tools specifically developed for Western settings, Pakistani students are exposed to a uniquely compounded stres

researcharxiv-cs-ai

Beyond Confidence: Stability-Aware Test-Time Adaptation for LLM Reasoning

arXiv:2609.11393v1 Announce Type: new Abstract: Test-time adaptation has emerged as a lightweight alternative to costly post-training for improving the reasoning capabilities of Large Language Models

local-aiarxiv-cs-ai

Beyond Static Guarantees: Measuring the Static-Pass Dynamic-Fail Gap in Security-Sensitive and LLM-Generated Python Code

arXiv:2609.10762v1 Announce Type: cross Abstract: Advances in large language models (LLMs) fuel the quest for scalable methods to assess the security of generated and security-sensitive software. Stat

Beyond Verified Answers: Solver-Informed Self-Distillation for Bootstrapping Operations Research Language Models

arXiv:2609.09957v1 Announce Type: cross Abstract: Modern large language models (LLMs) can translate natural-language descriptions into operations research (OR) formulations. Post-training techniques i

safetyarxiv-cs-ai

DeFiFusion: Combining Transaction Events with Smart Contracts to Detect Price Manipulation Attacks

arXiv:2609.11008v1 Announce Type: cross Abstract: Decentralized Finance (DeFi) has emerged as a rapidly growing blockchain-based financial service, where market transaction dynamics and underlying sma

Ecdysis: Efficient and Effective Training of Runtime Harnesses for LLM Agents

arXiv:2609.11677v1 Announce Type: cross Abstract: Self-evolving runtime harnesses can substantially improve the capabilities of large language model (LLM) agents and provide a promising paradigm for o

Exploring Multimodal Prompt for Visualization Authoring with Large Language Models

arXiv:2504.13700v2 Announce Type: replace-cross Abstract: Recent advances in large language models (LLMs) have shown great potential in automating the process of visualization authoring through simple

local-aiarxiv-cs-ai

Grounding Agent Memory: Environment-Probing Curation for Enterprise Agents

arXiv:2609.11060v1 Announce Type: new Abstract: Persistent memory is entering production-oriented agent platforms to help long-horizon agents accumulate experience across sessions. Yet a post-task cur

MOSAIC: Query-Aware Exploration Policy Adaptation for GraphRAG

arXiv:2609.11065v1 Announce Type: new Abstract: Graph Retrieval-Augmented Generation (GraphRAG) can connect evidence distributed across a corpus graph, but most systems use largely shared exploration

No-Box Vulnerability Analysis: Description-only Detection of Indirect Prompt Injection Vulnerabilities in MCP Servers

arXiv:2609.10854v1 Announce Type: cross Abstract: Conventional vulnerability analysis relies on either system access or dynamic interaction, all of which may be unavailable to third-party analysts aud

RouteRepair: Instance-Level Failure Diagnosis and Targeted Repair in LLM-Based Automated Heuristic Design for Routing Optimization

arXiv:2609.11452v1 Announce Type: new Abstract: Efficient routing optimization is essential to freight transportation, urban logistics, and shared mobility, where high-quality heuristics are often req

researcharxiv-cs-ai

Applications

Spectral Masking and Interpolation Attack (SMIA): A Black-box Adversarial Attack against Voice Authentication and Anti-Spoofing Systems

arXiv:2509.07677v5 Announce Type: replace-cross Abstract: Voice Authentication Systems (VAS) use unique vocal characteristics for verification. They are increasingly integrated into high-security sect

applicationsarxiv-cs-ai

TRUST-SQL: Tool-Integrated Multi-Turn Reinforcement Learning for Text-to-SQL over Unknown Schemas

arXiv:2603.16448v3 Announce Type: replace Abstract: Text-to-SQL parsing has achieved remarkable progress under the Full Schema Assumption. However, this premise fails in real-world enterprise environm

Verification of Adaptive Agentic Controllers through Finite Rule Revision

arXiv:2607.09770v2 Announce Type: replace Abstract: Industrial agentic AI systems increasingly exhibit a gap between prototype capability and production deployment. In particular, adaptive agents may

X-AuT: Progressive Audio-Encoder Compression for Speech LLMs with Cross-Scale Distillation

arXiv:2609.11412v1 Announce Type: cross Abstract: Reducing audio-encoder depth lowers the inference cost of speech large language models, but removing complete blocks perturbs the embeddings consumed

safetyarxiv-cs-ai

A Dynamic Fusion Large Language Model for Traffic Flow Prediction

model-releasesarxiv-cs-lg

arXiv:2609.11314v1 Announce Type: new Abstract: Traffic flow prediction is a core supporting technology for intelligent transportation systems. It uses historical data to infer future traffic dynamics

An Experimental Evaluation of Multimodal Prompt Injection Attacks on Agentic AI Frameworks

arXiv:2609.09404v1 Announce Type: cross Abstract: Agentic AI frameworks let a language model plan, keep memory, and call tools that reach real files, mail, and services. Most of these agents also read

Arbitrary Cipher Attacks Against Large Language Models Do Not Require Fine-Tuning

arXiv:2609.09553v1 Announce Type: cross Abstract: Large language model safety and security research is preoccupied with, among other things, detecting and preventing jailbreak attacks: alignment bypas

safetyarxiv-cs-ai

Artificial Intelligence Algorithms for the Detection of Pathologies Related to Lung Cancer through Image Analysis using Convolutional Neural Networks and Data Augmentation: a systematic mapping of the literature

arXiv:2609.10652v1 Announce Type: cross Abstract: Lung cancer is one of the leading causes of death worldwide, and its early diagnosis is crucial to improving patients prognosis and quality of life. H

Caption-once, Frames-on-Demand: Visual-Need Routing for Budget-Aware Agentic Long Video Understanding

arXiv:2609.11899v1 Announce Type: new Abstract: Long-video understanding on edge devices must reason over hours of content under tight compute and bandwidth budgets. Subsampling visual tokens loses te

agentsarxiv-cs-cv

Decision Shifts, Lost Label Functionality, and an Inconclusive Grounding Audit in Correctness-Gated Multi-Teacher Distillation

arXiv:2609.09702v1 Announce Type: new Abstract: Candidate decision correctness and rationale grounding are different objectives. We examine correctness-gated multi-teacher distillation in a fixed expe

Epistemic orientation predicts legislative effectiveness among members of the US Congress

arXiv:2609.11865v1 Announce Type: new Abstract: Truth and evidence-based communication provide important foundations for democratic governance, accountability, and collective decision-making. Prior wo

Evaluation of Vision-Language Models Across Diverse Coastal Environments

arXiv:2609.10855v1 Announce Type: new Abstract: Vision-language models (VLMs) enable robotic per- ception by associating visual observations with natural-language concepts. Yet their performance in co

safetyarxiv-cs-cv

Evidence for Limited Metacognition in LLMs

arXiv:2509.21545v3 Announce Type: replace Abstract: The possibility of LLM self-awareness and even sentience is gaining increasing public attention and has major safety and policy implications, but th

safetyarxiv-cs-lg

Explainability Assistant: A Conversational XAI Interface for Interpreting Energy Consumption Models

arXiv:2609.11860v1 Announce Type: cross Abstract: Energy consumption forecasting relies on increasingly complex machine learning (ML) models, such as Genetic Programming-based symbolic regressors, who

researcharxiv-cs-lg