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When Do Large Language Models Exhibit Unsolicited Deception?

arXiv:2504.00285v2 Announce Type: replace Abstract: Large Language Models (LLMs) are effective at deceiving when prompted to do so. Models that demonstrate better performance on reasoning tasks are al

agentsarxiv-cs-cl

When Does Defendant Statement Matter? A Study of Bias and Persuasion in LLM-Simulated Jurors

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DGX agent

arXiv:2609.09887v1 Announce Type: new Abstract: LLMs have been used to simulate human decision-making in professional settings, yet their behaviors in common-law jury trials remain unexplored. We stud

model-releasesarxiv-cs-cl

10 Sept 2026

When Does Low-Bit Quantization Preserve the Decisions of Vector Search?

arXiv:2609.09854v1 Announce Type: cross Abstract: Low-bit quantization can achieve high recall on some vector representations and fail sharply on others, while average distortion and global rank corre

When Does Memory Help? A Cost-Aware Evaluation of Long-Term Memory in Tool-Using LLM Agents

arXiv:2609.05441v1 Announce Type: new Abstract: Long-term memory for LLM agents is evaluated today by conversational recall benchmarks (LoCoMo, LongMemEval), which measure question answering over dial

When Fusion Fails: Corruption-Aware Rebalanced Fusion for Multi-Modal Medical Image Segmentation

arXiv:2609.10261v1 Announce Type: new Abstract: Multi-modal medical image segmentation leverages complementary diagnostic information, yet fusion can underperform single-modality baselines when spatia

safetyarxiv-cs-cv

When Intelligence Becomes Agency: A Theory of Governed, Proactive Agency for Symbiotic AI Systems

arXiv:2609.07741v1 Announce Type: new Abstract: Persistent AI assistants are intended to extend human attention, memory, and coordination across changing digital and physical environments. To be truly

When Tools Hurt LLM Reasoning: State-Dependent Belief Revision under External Evidence

arXiv:2508.15754v2 Announce Type: replace-cross Abstract: Tool use is often assumed to monotonically improve reasoning, where external evidence is expected to help when relevant and be ignored when ir

local-aiarxiv-cs-ai

Where Does the Sound Go? Tracing Acoustic Information Loss in Audio-Conditioned LLMs

arXiv:2609.05871v1 Announce Type: cross Abstract: Audio-conditioned language models often underuse acoustic cues such as prosody, emotion, and non-speech sounds, raising the question of whether ASR-su

Which Medical Questions Deserve Rationales? Perturbation-Sensitive Selection for Robust QA

arXiv:2609.09684v1 Announce Type: new Abstract: Medical question-answering datasets often contain answer labels, whereas high-quality rationales remain scarce, noisy, or costly to validate. This chang

researcharxiv-cs-cl

Who Are They to Each Other? Multi-Agent Reasoning for Speaker Relationship Inference

arXiv:2609.09628v1 Announce Type: cross Abstract: Inferring speaker relationships from spoken conversations is an important step towards socially aware speech understanding. However, this task remains

agentsarxiv-cs-cl

Who Argues What? Joint Argument-Entity Detection and Classification in Political Debates

arXiv:2609.10192v1 Announce Type: new Abstract: Political debates are often analyzed through Argument Mining (AM) to investigate the key arguments that drive them. However, political arguments are rar

researcharxiv-cs-cl

Who Laughs with Whom? Disentangling Influential Factors in Humor Preferences across User Clusters and LLMs

arXiv:2601.03103v2 Announce Type: replace-cross Abstract: Humor preferences vary widely across individuals and cultures, complicating the evaluation of humor using large language models (LLMs). In thi

researcharxiv-cs-ai

Who Maintains Agent Skills? A Longitudinal Study of Human-Governed, AI-Assisted Skill Maintenance

arXiv:2609.05677v1 Announce Type: cross Abstract: Lifelong LLM agents increasingly rely on external skill artifacts as one element for preserving and reusing capabilities over time. These skills (usua

agentsarxiv-cs-ai

Why Do LLM Agents Fail in Exploring New Environments? A World-Modeling Perspective

arXiv:2510.15047v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) as agents often fail to improve in new environments. We identify and characterize a failure mode we call explorat

safetyarxiv-cs-cl

Why Is Video Still So Expensive? A Survey of Inference-Efficiency Mechanisms in Video and Audiovisual LLMs

model-releasesarxiv-cs-cl

arXiv:2609.10355v1 Announce Type: cross Abstract: Video understanding has rapidly evolved toward video large language models (VideoLLMs): systems that couple video representations with pretrained larg

Why Learning Rediscovers the Closed-Form Diagonal Regularizer

arXiv:2609.09656v1 Announce Type: cross Abstract: We identify a diagonal saturation principle in modal inverse problems: when truncation noise is isotropic, the Bayes-optimal Tikhonov shape is a close

Why the public needs to step up. I talk with @CBCNews about why a (temporary) boycott of generative AI, as unlikely as it is, ought to be on…

Why the public needs to step up. I talk with @CBCNews about why a (temporary) boycott of generative AI, as unlikely as it is, ought to be on the table. https://youtu.be/3BBp-tCvsOM?si=88KxNluVZnuzRw3L

safetygary-marcus--x

WolfSociety: Understanding Collective Risk from Harmful-Agent Scaling in Financial Agent Societies

arXiv:2609.05591v1 Announce Type: cross Abstract: Safety evaluations typically focus on individual agents, but interacting agents can spread harmful information and influence the environment in which

World Models Under Asynchronous Sensor Observations

arXiv:2609.07299v1 Announce Type: new Abstract: Learned world models typically assume that observations arrive synchronously, an abstraction inherited from simulators that return a complete state vect

researcharxiv-cs-ai

World-Time Compute with Verified Code World Models

arXiv:2609.09163v1 Announce Type: new Abstract: LLMs generalize across a domain only after seeing many real, labeled examples, which most domains lack. We study a way to manufacture it cheaply. When a

WorldAgen: Unified State-Action Prediction with Test-Time World Model Training

arXiv:2609.08162v1 Announce Type: new Abstract: How can vision-language-action (VLA) models adapt to new environments where world dynamics shift? While recent research has combined world modeling and

agentsarxiv-cs-ai

Applications

X-amine509: Predicting the Practical Risk Level of Enterprise X.509 Certificates

arXiv:2609.09402v1 Announce Type: cross Abstract: Enterprises managing large X.509 certificate inventories face a prioritization problem: deterministic analysis tools that precisely identify standards

applicationsarxiv-cs-lg

X-CoSD: Communication-Efficient Cross-Vocabulary Collaborative Speculative Decoding

arXiv:2609.09166v1 Announce Type: new Abstract: This paper investigates collaborative speculative decoding (CoSD), a distributed large language model (LLM) inference framework in which an on-device sm

local-aiarxiv-cs-cl

X2-NativeCursor: Native-Token Text Progress Tracking for Incremental-Text Streaming Codec TTS

arXiv:2609.09677v1 Announce Type: new Abstract: Incremental-text streaming text-to-speech (TTS) needs online text progress tracking for synchronized highlighting, interruption handling, and dialogue-h

safetyarxiv-cs-cl

X2Streaming-ASR: wait when uncertain, emit when ready for streaming ASR

arXiv:2609.08672v1 Announce Type: cross Abstract: Streaming automatic speech recognition (ASR) for real-time voice agents and full-duplex dialogue must provide accurate partial transcripts with low co

XAI-Refine: An Automated Explanation-Knowledge Loop for Brain-Age Prediction

arXiv:2609.09388v1 Announce Type: new Abstract: Brain-age prediction models are commonly evaluated by predictive accuracy, yet accurate predictions alone do not establish that a model relies on reprod

safetyarxiv-cs-lg

XAI-SDN: An Explainable Entropy-Guided Machine Learning Framework for Real-Time DDoS Detection in Software Defined Networks

arXiv:2609.05701v1 Announce Type: cross Abstract: One of the biggest risks faced by Software Defined Networks (SDN) is the Distributed Denial of Service (DDoS) attack in which a compromised controller

xDailyBench: Benchmarking LLMs on Professional Consultation for Real-Life Problems

arXiv:2609.07784v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used for everyday assistance, yet existing benchmarks only partially reflect the requests users naturally

XYBench: Can LLMs Respond Pragmatically to Queries with Misconceptions?

arXiv:2609.06842v1 Announce Type: cross Abstract: When non-expert users ask LLMs for assistance, their queries can often have misconceptions (e.g., 'How do I parse XML with regex?'). In such cases, of

YallaMorph: A Benchmark for Evaluating Arabic Morphological Generation in Large Language Models

model-releasesarxiv-cs-cl

arXiv:2609.10153v1 Announce Type: new Abstract: Arabic morphology remains challenging for large language models, since fluent generation does not guarantee accurate morphosyntactic control. Existing A

You Are What You Read: Misalignment via In-Context Persona Induction

arXiv:2609.06851v1 Announce Type: cross Abstract: Broad misalignment has been produced by finetuning on narrow data, harmful or benign, and in context only by demonstrations of the undesirable behavio

researcharxiv-cs-ai

You can also create editable financial models, research notes, and pitchbooks using your firm's own Excel, Word, and PowerPoint templates.

OpenAI now supports generating fully editable financial models, research notes, and pitchbooks directly in a firm’s existing Microsoft Office templates (Excel, Word, PowerPoint). Documents are created

model-releasesopenai--x

Your Agent Says Yes: Interpreting Adversarial Market Behavior Beyond Individual Transactions

arXiv:2609.07675v1 Announce Type: cross Abstract: Transaction-local controls answer whether one financial request may proceed, but market behavior can be distributed across messages, agents, assets, a

local-aiarxiv-cs-ai

Zero-Shot Temporal Localisation of Audio Deepfakes in Multi-Speaker Conversations

model-releasesarxiv-cs-lg

arXiv:2609.10051v1 Announce Type: cross Abstract: Voice-cloning fraud increasingly relies on surgical injection: a genuine conversation in which only one or two sentences are replaced by synthetic spe

zScore-N: A Neural Network for On-Chain Wallet Reputation Scoring

arXiv:2609.08247v1 Announce Type: new Abstract: Wallet reputation scores decide who receives an airdrop, who can borrow, and who enters an allowlist across decentralised finance. They almost always be

1-bit 27B in the browser: 25–30 tok/s on a 6 GB RTX 3060 Laptop (WebGPU, no install)

model-releasesr-localllama

mentria.ai is a browser inference engine I've been building solo, from scratch in WebGPU/WGSL. This week it crossed a milestone I had been chasing for a while: a 27B one-bit model answering at up to 3

3DHarnessBench: Probing Agentic 3D-to-Code Capabilities of Frontier Vision-Language Models

model-releasesarxiv-cs-cv

arXiv:2609.06535v1 Announce Type: new Abstract: We introduce 3DHarnessBench, a benchmark that evaluates the agentic ability of frontier vision-language models (VLMs) to recover 3D geometry as Blender

3DWay: Generalizing Robot Manipulation via 3D Consistent Waypoints

model-releasesarxiv-cs-ro

arXiv:2609.08224v1 Announce Type: new Abstract: Intermediate representations are key to bridging the modality gap between generalizable manipulation policies and large-scale pretrained vision-language

A Better Spur Should Start From Each Objective

arXiv:2609.08211v1 Announce Type: cross Abstract: Real-world Multi-Objective Reinforcement Learning (MORL) often suffers from sparse rewards, reward conflicts, and late-stage reward tug-of-war, causin

safetyarxiv-cs-lg

A Black-Box Adversarial Attack on Human Pose Estimation and Keypoint-Based Action Recognition Models

arXiv:2609.08013v1 Announce Type: new Abstract: Human pose estimation and keypoint-based action recognition models are increasingly deployed as components of video understanding pipelines, yet their v

researcharxiv-cs-cv

A Brain-inspired Hierarchical Framework for Zero-Shot Robot Task Reasoning and Execution

arXiv:2609.05985v1 Announce Type: new Abstract: Robots that follow open-ended language instructions need to connect semantic intent to visual scene understanding, geometric feasibility, object states,

researcharxiv-cs-ro

A budget-dependent crossover between coverage- and response-based training-set selection for machine-learned interatomic potentials

arXiv:2609.05877v1 Announce Type: new Abstract: Selecting compact training sets for machine-learned interatomic potentials requires deciding whether to preserve structural diversity or target configur

A Closed-Form Estimator and Diagnostic Battery for Anchor-Judge Error Correlation, Under a Single-Common-Factor Model

arXiv:2609.08826v1 Announce Type: cross Abstract: When an external reference set (an anchor) is used to decompose an LLM-judge panel's error into a quality signal and a shared common-mode error, stand

safetyarxiv-cs-lg

A Cloud-Based Hybrid Model for Real-Time Detection of BRTA-Approved Licence Plates Using YOLO Tiny and Haar Cascade

arXiv:2609.06507v1 Announce Type: new Abstract: Accurate vehicle license plate detection is essential for applications such as intelligent transportation systems, toll collection, parking management,

local-aiarxiv-cs-cv

A Comparative Study of GAN-Based Deep Learning Models for Pneumonia Detection in Chest X-Rays

arXiv:2609.06276v1 Announce Type: new Abstract: This study evaluates pneumonia classification in chest X-rays using VGG19, MobileNetV2, ResNet50, and a custom CNN, and explores Generative Adversarial

researcharxiv-cs-cv

A Controlled Comparison of Manual and Teleoperated Intraocular Instrument Motion for an Input Device

arXiv:2609.08770v1 Announce Type: new Abstract: Input devices for robotic microsurgery are frequently described as preserving the surgeon's trained technique, but the claim is rarely measured. We comp

researcharxiv-cs-ro

A dictionary learning framework for graphs via filters and optimal transport

model-releasesarxiv-cs-lg

arXiv:2609.05919v1 Announce Type: new Abstract: We propose a graph dictionary learning (GDL) framework where each graph is represented as a zero-mean Gaussian distribution derived from its filtered La

A Distributed Consensus Particle Filter for Target Tracking using Autonomous Surface Vessels

arXiv:2609.09066v1 Announce Type: new Abstract: Maritime target tracking over large distances often requires multi-agent teams without centralized coordination, and intermittent communication. Each ag

agentsarxiv-cs-ro