Search: “gpt”

The human-authorship halo: attribution bias in literary style evaluation by humans and AI

arXiv:2510.08831v2 Announce Type: replace Abstract: As AI writing tools become widespread, we need to understand how both humans and machines evaluate literary style, a domain where objective standard

10 Sept 2026

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Typed Federated Artifacts for the Agentic Web:Sharing Tool-Routing Knowledge Across Frozen,Heterogeneous LLM Agents

DGX agent

arXiv:2609.06815v1 Announce Type: cross Abstract: An open, networked web will allow agents to run frozen models from multiple vendors, keep their history private, and teach each other which tool to ca

model-releasesarxiv-cs-ai

10 Sept 2026

A Measurement Study of LLM Inference Trade-offs Across Edge Continuum Hardware

arXiv:2609.08307v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used as backends for intelligent web services, but serving them across the edge continuum requires balan

Local Ai

Beyond the Matrix Sign: Quadratic Spectral Descent

arXiv:2609.07597v1 Announce Type: new Abstract: Muon can be interpreted as optimizing a linear local objective over a spectral-norm ball. This gives a matrix-sign update that preserves the singular di

local-aiarxiv-cs-lg

Beyond the Verdict: Evidence-Aligned Evaluation of Visual Prompt-Injection Guardrails

arXiv:2609.05535v1 Announce Type: new Abstract: Verdict-only evaluation does not reveal whether a vision-language model (VLM) used the visual evidence that should support its decision. We study this p

Damage-Aware Bandit Pruning for Vision and Language Transformers

arXiv:2609.05448v1 Announce Type: cross Abstract: Structured post-training pruning of transformers requires selecting complete functional units whose suppression causes limited degradation. We formula

Evaluating Vision-Language Models for Image Quality Assessment using Psychophysical Data

arXiv:2603.24578v2 Announce Type: replace Abstract: Psychophysical experiments remain the most reliable approach for perceptual image quality assessment (IQA), yet their cost and limited scalability m

From LLM-Generated Specifications to Learned Quadruped Locomotion

model-releasesarxiv-cs-ro

arXiv:2609.07111v1 Announce Type: new Abstract: Quadruped robot locomotion policies are often trained using reinforcement learning, which in turn relies heavily on hand-crafted reward functions. Desig

GradeTrap: Authority Cues in Images Shift VLM Judgments Despite Explicit Instructions to Ignore Them

arXiv:2609.06058v1 Announce Type: new Abstract: As vision-language models (VLMs) become increasingly capable and are deployed in consequential real-world settings, they must evaluate evidence independ

Inducing Emergent Misalignment from Reward Hacks with Iterative DPO

arXiv:2609.06649v1 Announce Type: new Abstract: Reward hacking during reinforcement learning from verifiable rewards (RLVR) can induce reward seeking and broad misalignment in language models. Studyin

PAC-Private Autoregressive Generation: Calibrating Noise to Ensemble Disagreement

arXiv:2609.05676v1 Announce Type: new Abstract: Language models adapted on private text are often served through APIs, so privacy leakage occurs through generated outputs rather than exposed weights.

researcharxiv-cs-lg

Parallelism Strategy Chaining for Fast Training Convergence

arXiv:2609.07236v1 Announce Type: new Abstract: Selecting a parallelism strategy - the configuration of data, tensor, and pipeline parallelism degrees together with micro- and global-batch sizes - lar

SAFIRE: Safety-Critical Benchmark for Fine-grained Fire and Smoke Understanding in Multimodal LLMs

arXiv:2609.07823v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) show strong progress on vision-language tasks, yet their reliability in safety-critical settings remains undere

SeRV: Semantic-Aligned Residual Vector Quantization for American Sign Language Generation

arXiv:2609.05742v1 Announce Type: new Abstract: American Sign Language (ASL) generation remains challenging due to limited paired text-ASL motion data and the difficulty of learning motion representat

TimeBlind: A Spatio-Temporal Compositionality Benchmark for Video LLMs

arXiv:2602.00288v4 Announce Type: replace Abstract: Fine-grained spatio-temporal understanding is essential for video reasoning and embodied AI. Yet, while Multimodal Large Language Models (MLLMs) mas

Safety

A Structured Debate-Mixture-of-Agents Framework for Complex Clinical Diagnostic Decision Support

arXiv:2609.05069v1 Announce Type: cross Abstract: Large language models (LLMs) show potential for medical tasks, but their single-turn question-answer format does not reflect how clinical diagnosis is

safetyarxiv-cs-ai

Harbor Adapters and Harbor-Index: Infrastructure and a Curated Meta-Dataset for Large-Scale Agentic Evaluation

arXiv:2609.04298v1 Announce Type: new Abstract: Evaluating agents on the growing number of agentic benchmarks is challenging because they often require complex environments and agent integrations. We

Agents

HarvestBench: Measuring Whether LLM Agents Will Pay to Avoid Killing Animals

arXiv:2609.04444v1 Announce Type: new Abstract: Benchmarks for the side effects an agent causes on the way to a goal already exist, but HarvestBench is the first to put a price on avoiding the side ef

agentsarxiv-cs-ai

Large Language Models with At Most One Spike per Neuron

arXiv:2609.05151v1 Announce Type: cross Abstract: Leveraging their inherent sparse event-driven computation, spiking neural networks (SNNs) offer a promising path toward energy-efficient large languag

researcharxiv-cs-cl

Necessary or Sufficient? Evaluating LLM Explanations With Behavioural Evidence

arXiv:2609.05385v1 Announce Type: new Abstract: LLM decision components that can operate within agent workflows often produce action-relevant recommendations or judgements together with explanations.

PerfReasoning: How Well Do LLMs Reason on Hardware Performance?

arXiv:2609.04476v1 Announce Type: new Abstract: Performance modeling is central to hardware design and software optimization, yet constructing these models requires structured reasoning about computat

Repeat-After-Me: Black-Box Adaptive Visual Prompt Injection

arXiv:2609.04533v1 Announce Type: cross Abstract: Prompt injection is widely recognized as a major security threat to AI agents that interact with untrusted external data, such as websites, documents,

Retinal OCTA Phenotyping with LLM Reporting for Alzheimer's Disease

arXiv:2609.04689v1 Announce Type: cross Abstract: Early identification of Alzheimer's disease (AD) remains challenging because established assessment methods can be costly, resource-intensive, or unsu

Adapting to Evolving Requirements: Agentic AI for Retail Supply Chain Operations

arXiv:2609.03860v1 Announce Type: new Abstract: Retail supply chain operations rely on coupled decision modules that must adapt as requirements evolve. LLMs offer a natural-language interface for this

Safety

DuplexSpeechBench-IFEval: Evaluating Implicit Instruction Following in Full-Duplex Voice Agents

arXiv:2609.03423v1 Announce Type: new Abstract: Full-duplex voice agents must continuously decide when to listen, backchannel, interrupt, handle speech overlaps, take the floor, and yield. Existing be

safetyarxiv-cs-ai

Environment Evolution for Terminal Agents

arXiv:2609.04128v1 Announce Type: new Abstract: Scaling interactive and verifiable environments is critical for training terminal agents. As frontier models become more capable, environments synthesiz

IRWOZ 2.0: A Large Language Model-driven Dialogue Dataset for Industrial Robot Conversations

arXiv:2609.04030v1 Announce Type: new Abstract: IRWOZ has improved industrial human-robot interaction (HRI) dialogue systems through domain-specific annotations. However, its initial version contains

Measuring Harmfulness of Computer-Using Agents

arXiv:2508.00935v3 Announce Type: replace-cross Abstract: Computer-using agents (CUAs), which can autonomously control computers to perform multi-step actions, might pose significant safety risks if m

ObserverBench: Testing Mechanistic Estimates for Intervention and Control

arXiv:2609.03026v1 Announce Type: cross Abstract: Mechanistic interpretability is increasingly used to guide interventions such as activation steering, circuit removal, and safety monitoring. Yet an i

Persistent Identity Preservation in Generative Image Models: A Benchmark and Evaluation System

arXiv:2609.04151v1 Announce Type: new Abstract: Generative image models can now produce high-quality images, follow complex instructions, and support precise edits, but they still struggle to preserve

Privacy-Preserving Heterogeneous Multi-LLM Federated Inference for Cognitive Diagnosis

arXiv:2609.02947v1 Announce Type: cross Abstract: Significant challenges remain in AI-driven educational systems in balancing privacy preservation with accurate cognitive diagnosis. To overcome this,

The Gradient Does Not See Rank: Rank-Indifference in Matrix-CODI on ProsQA

arXiv:2609.03090v1 Announce Type: new Abstract: Continuous chain-of-thought models compress reasoning into latent tokens. Matrix-valued variants, which route each latent token through a d x d matrix b

researcharxiv-cs-lg

When Models Edit Too Much: On the Fidelity of Minimal Code Edits

arXiv:2609.04061v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used to edit existing code, but correctness alone is not enough: useful repairs should also be minimal,

WorldReward: Reward Modeling for Camera-Conditioned World Models

arXiv:2609.03952v1 Announce Type: new Abstract: Camera-conditioned world models generate interactive videos in which commanded actions should induce the expected scene changes while appearance, geomet

Agents

You Can't Escape Your Own Activations : Evaluation Awareness and Multi-Agent Monitoring

arXiv:2609.03035v1 Announce Type: cross Abstract: LLM agents are increasingly deployed in multi-agent systems, where they can collude while keeping their actions benign. Output monitors designed to de

agentsarxiv-cs-lg

APEx: Distillation of Agent Procedural Experience for Adaptive Deep Research Question Answering

arXiv:2609.02253v1 Announce Type: new Abstract: Deep research agents augment large language models with external tools to answer complex, long-horizon questions through multi-turn reasoning. Learning

Beauty is in the AI of the beholder: MLLMs systematically overrate facial attractiveness

arXiv:2609.02512v1 Announce Type: new Abstract: Beauty assessments from Multimodal Large Language Models (MLLMs) are increasingly popular amongst users, companies, and aestheticians. This raises the q

Safety

Do Cantonese-Adapted Language Models Better Predict Cantonese Reading? A Cross-Model Eye-Tracking Evaluation

arXiv:2609.02163v1 Announce Type: new Abstract: Information-theoretic measures derived from autoregressive language models are widely used to characterize the expectations that shape human reading, bu

safetyarxiv-cs-cl

Do Large Language Models Capture the Diversity in their Training Data?

arXiv:2609.02275v1 Announce Type: cross Abstract: Large language models are trained to model conditional distributions over text, yet it remains inadequately understood whether they capture the full d

researcharxiv-cs-ai

FUSE: An Evaluating Framework for Dangerous Capabilities of LLMs

arXiv:2609.02168v1 Announce Type: new Abstract: Fragmented safety evaluation undermines the governance of dangerous AI capabilities. We present a modular framework that evaluates each model through th

Harness Engineering in LLM Tool Use via Agent-Native Reusable Tool Primitives

arXiv:2609.01736v1 Announce Type: cross Abstract: Large language models (LLMs) augmented with external tools have demonstrated remarkable capability in solving complex real-world tasks. However, exist

HEAT: Faster Fully Homomorphic Inference via Approximations-Weights Co-Adaptation

arXiv:2609.01730v1 Announce Type: cross Abstract: Fully homomorphic encryption (FHE) allows a server to run a language model directly on encrypted user prompts, but current approaches remain prohibiti

researcharxiv-cs-ai

How LLMs Build Fictional Worlds: Setting and Narrative Space in AI-Generated Creative Storytelling

arXiv:2609.02482v1 Announce Type: new Abstract: In this paper, we analyze how Large Language Models (LLMs) employ worldbuilding strategies, focusing on setting as one measurable dimension of storyworl

LeakageBench: Document-Level Leakage Risk for Redacting Personally Identifiable Information in Document Images

arXiv:2609.02207v1 Announce Type: cross Abstract: Real-world personally identifiable information (PII) redaction often operates on document images---scans, screenshots, and PDF renderings---where OCR

Public-Sharing Labels and Verbatim Field Egress in an MCP-to-A2A Agent Configuration: A Controlled Multi-Model Study

arXiv:2609.01693v1 Announce Type: cross Abstract: Safety properties assessed separately for Model Context Protocol (MCP) tool use and Agent2Agent (A2A) delegation need not describe behavior when one a

Rendering-in-the-Loop: An Execution-Driven Agent for Interactive Web Development

arXiv:2609.02088v1 Announce Type: new Abstract: Multimodal large language models have achieved remarkable progress in front-end web development, generating interactive webpages from multimodal referen

Repo-To-Skill: Distilling GitHub Repositories Into AI4AI Skills

arXiv:2609.02749v1 Announce Type: new Abstract: Autonomous agents are beginning to carry out machine-learning (ML) research end to end. These agents combine a model backbone with a harness for plannin

TalkFa: A Unified Benchmark for Farsi Dialogue Generation and Understanding

arXiv:2609.01810v1 Announce Type: new Abstract: Farsi, spoken by more than 120 million people, lacks a comprehensive benchmark for dialogue generation and understanding. We introduce TALKFA, a unified