Search: “gpt”

ViFA-Council: Multi-Agent LLM Deliberation for Vietnamese Folk Art Generation

arXiv:2609.13348v1 Announce Type: cross Abstract: This paper presents ViFA-Council, a three-stage multi-agent framework that employs multiple large language models (LLMs) to tackle two culturally comp

15 Sept 2026

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When Can You Trust Your Synthetic Users? Diagnostics and Corrections for LLM Consumer Panels

DGX agent

arXiv:2609.13148v1 Announce Type: cross Abstract: Large language models are increasingly deployed as synthetic consumer panels, promising 97% cost reductions over traditional surveys. Yet aggregate va

model-releasesarxiv-cs-lg

15 Sept 2026

When Consistency Does Not Mean Reliability: Evaluating Local LLM Judges Against Human Ratings

arXiv:2609.13824v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used to evaluate the responses of other language models. This approach, known as LLM-as-a-Judge, is faster

15 Sept 2026

Automated Detection and Structuring of Social Tipping Point Evidence in Climate related Documents: A Modular AI Framework

arXiv:2609.12254v1 Announce Type: new Abstract: The climate literature has grown faster than review teams can read it. That gap matters most for a concept like the environmental social tipping point,

Earth-Agent-Pro: Towards Real-World Full-Chain Earth Observation with Agents

arXiv:2609.12533v1 Announce Type: cross Abstract: Real-world Earth observation (EO) agents must translate high-level scientific questions into executable workflows to acquire observations, prepare dat

Is Bash All You Need? An Empirical Study of Tool Interfaces for Enterprise Digital Worker Agents

arXiv:2609.11999v1 Announce Type: cross Abstract: In this study, we examine whether a general shell can outperform specialized tools on enterprise tasks. Shell-based agents have shown strong results i

ORQA: An Occupation-Realistic Question and Answer Framework for LLM Professional Knowledge

arXiv:2609.12366v1 Announce Type: new Abstract: We present ORQA, a method for testing occupation-level knowledge in large language models. Prior methods either map abstract LLM skills to occupations v

Rank-Efficient LoRA via Joint Tangent-Space Optimization under Isotropic Curvature

arXiv:2609.12123v1 Announce Type: new Abstract: Low-Rank Adaptation (LoRA) is an effective approach for adapting large pretrained models by learning low-rank weight updates. In practice, the LoRA rank

Semantically Aligned Gradient-Driven Context-Preserving Image Editing

model-releasesarxiv-cs-cv

arXiv:2609.12691v1 Announce Type: new Abstract: Instruction-guided image editing has a training-time blind spot. Generative editors are never required to semantically verify whether their outputs actu

Tasks over Application Manuals: Revealing Gaps in Long-Horizon Procedural Reasoning for Language Models

arXiv:2609.13005v1 Announce Type: new Abstract: Large language models (LLMs) have achieved strong performance on a wide range of natural language tasks, and recent benchmarks suggest that they are inc

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

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

NovGauge: A Fine-Grained Benchmark for Diagnosing LLMs' Capability in Paper Novelty Assessment

arXiv:2609.11234v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used in peer review at major AI conferences, yet novelty remains a persistent weak point. Existing benchma

12 Sept 2026

Prompt Revision as a Source of Cultural Bias in Text-to-Image Systems

arXiv:2609.11532v1 Announce Type: new Abstract: Commercial text-to-image systems silently revise user prompts before generating images, a step users typically cannot disable or even see. Yet, existing

12 Sept 2026

SemVerBench: Benchmarking LLM Comprehension of Version-Constraint Resolution Semantics

arXiv:2609.11180v1 Announce Type: new Abstract: Large language model (LLM) coding agents constantly decide whether a version satisfies a constraint such as ^1.2.3 or >=2.0,1.2 means >=1.3.0) traps eve

12 Sept 2026

Black-Box Membership Inference via Word-Level Probability Estimation

arXiv:2609.10611v1 Announce Type: cross Abstract: Membership inference attacks (MIAs) have emerged as critical tools for auditing privacy risks in large language models (LLMs), aiming to determine whe

Inverse Turing Bench: Evaluating Language Models as Judges of Human vs. AI Dialogue

arXiv:2606.21844v2 Announce Type: replace Abstract: As AI systems integrate into online spaces, differentiating them from humans in conversations is increasingly important. We present Inverse Turing B

Multilingual in Name Only? Cultural and Linguistic Weaknesses of LLMs in Urdu

arXiv:2609.10758v1 Announce Type: new Abstract: Multilingual large language models (LLMs) are increasingly used for open-ended text generation, yet their behaviour in low-resource languages remains po

Research

On the Impact of Anonymization on the Performance of Large Language Models

arXiv:2609.11335v1 Announce Type: new Abstract: As large language models are increasingly deployed in sensitive domains, anonymizing input data to protect personally identifiable information has becom

researcharxiv-cs-cl

Agents

OpenResearcher: A Fully Open Pipeline for Long-Horizon Deep Research Trajectory Synthesis

arXiv:2603.20278v2 Announce Type: replace-cross Abstract: Training deep research agents requires long-horizon trajectories that interleave search, evidence aggregation, and multi-step reasoning. Howev

agentsarxiv-cs-cl

RelayS2S: A Dual-Path Speculative Generation for Real-Time Dialogue

arXiv:2603.23346v2 Announce Type: replace Abstract: Real-time spoken dialogue systems face a fundamental tension between latency and response quality. End-to-end speech-to-speech (S2S) models respond

Research

Rethinking Verbalized Confidence for LLM-as-a-Judge: A Compatibility Shift on Post-2025 Proprietary Models

arXiv:2609.10996v1 Announce Type: new Abstract: Verbalized confidence, long dismissed as overconfident, coarse, and prone to round-number clustering, is now the more robust soft-scoring mechanism for

researcharxiv-cs-cl

SGA: Plug&Play Geometric Verification for Educational Video Synthesis

model-releasesarxiv-cs-cv

arXiv:2607.18116v2 Announce Type: replace-cross Abstract: Recent work leverages Large Language Models (LLMs) to generate executable code for pedagogical animations using libraries such as Manim. Howev

Story Imprinting: AI Assistants Absorb Traits from Human Characters They Resemble

arXiv:2609.10883v1 Announce Type: cross Abstract: Language models are trained to implement a helpful AI Assistant character (e.g., Claude). We explore how finetuning on synthetic stories affects this

Safety

Structural Process Supervision for Latent Chain-of-Thought Reasoning

arXiv:2609.09928v1 Announce Type: new Abstract: Latent reasoning approaches enhance token-level efficiency and robustness by replacing verbose, explicit chain-of-thought (CoT) tokens with compact cont

safetyarxiv-cs-ai

Structurally Speaking: Motif-Oriented Graph Captioning through Bidirectional Graph-Text Translation

arXiv:2609.10923v1 Announce Type: new Abstract: Graph captions should help readers understand graph structure, rather than simply translate adjacency matrices into long textual edge lists. A useful gr

T1: Terminal Agent Reinforcement Learning for Long-Horizon Tasks

arXiv:2609.11042v1 Announce Type: new Abstract: Agent usage is shifting toward long-horizon tasks such as coding and scientific discovery, among which terminal tasks are especially important. We intro

3rd Place Solution to Human Motion Challenges in Real-World and Clinical Settings (MoCha) @ECCV2026: Language-Aligned Motion Representations for Domain-Generalizable UPDRS-Gait Severity Estimation

model-releasesarxiv-cs-cv

arXiv:2609.10187v1 Announce Type: new Abstract: In this work, we introduce language-aligned motion representations for domain-generalizable UPDRS-Gait severity estimation, aiming to learn semantically

Agentic ML Exploration (A-MLE) for Ads Ranking

arXiv:2609.08248v1 Announce Type: new Abstract: Modern industrial ads ranking stacks are increasingly bottlenecked not by model capacity or training compute, but by the throughput of human ML iteratio

Alignment Whack-a-Mole : Finetuning Activates Verbatim Recall of Copyrighted Books in Large Language Models

arXiv:2603.20957v4 Announce Type: replace-cross Abstract: Frontier LLM companies have repeatedly assured courts and regulators that their models do not store copies of training data. They further rely

AtomCite: Verification and Correction of Supplied Page-Level Citations in Multi-Page Documents

arXiv:2609.05802v1 Announce Type: cross Abstract: Large language models answering questions over multi-page documents are expected to cite the supporting pages, yet supplied citations are sometimes in

Audio-Maestro: Enhancing Large Audio-Language Models with Tool-Augmented Reasoning

arXiv:2510.11454v2 Announce Type: replace-cross Abstract: Recent advancements in large multimodal models (LMMs) have shown strong capabilities in audio understanding. However, most systems rely solely

Benchmarking Hybrid Deep Research Across Database Querying and Web Search

arXiv:2609.09410v1 Announce Type: new Abstract: While autonomous agents have made significant strides in 'deep research' by iteratively navigating the open web to synthesize information, real-world pr

Closing the Consistency Gap: Self-Evolving Agents That Learn to Stay on Course

arXiv:2609.08832v1 Announce Type: new Abstract: Large language model (LLM)-powered agents can be accurate on average yet unreliable in production, a discrepancy that has been observed but remains larg

DSAEval: Evaluating Data Science Agents on a Wide Range of Real-World Data Science Problems

arXiv:2601.13591v3 Announce Type: replace Abstract: Recent LLM-based data agents aim to automate data science tasks ranging from data analysis to deep learning. However, the open-ended nature of real-

Edu-QuRating: Multi-Dimensional Educational Data Curation with Distilled Pairwise Judgements

arXiv:2609.09425v1 Announce Type: new Abstract: Educational data filters have become a practical way to improve language-model pre-training, but most filters treat educational value as a single scalar

EmoMed: An Emotionally-Aware Agent for Multimodal Medical Support with Real-Time Information Retrieval

arXiv:2609.07194v1 Announce Type: new Abstract: We present EmoMed - a multimodal medical consultation agent that adapts its responses based on users' emotional states while maintaining clinical accura

ExecCritic: Learn to Test, Test to Improve for Coding Agents

arXiv:2609.09133v1 Announce Type: new Abstract: Execution feedback can guide coding agents toward correct repository repairs, but only when the tests capture the behavior requested by the issue. Agent

FATS: A Prompt Injection Attack Utilizing Feign Security Agents with Deceptive Few-shots Learning

arXiv:2410.08776v3 Announce Type: replace-cross Abstract: Large Language Models (LLMs) face significant security risks despite their advanced capabilities. While techniques like Reinforcement Learning

How AI Models Manage Epistemic Authority: A Taxonomy and Comparative Analysis of Responses to User Disagreement

arXiv:2609.07662v1 Announce Type: cross Abstract: Large language models are increasingly used as sources of advice and information, including in high-stakes settings, yet little is known about how the

LogiScope-VQA: Benchmarking Vision-Language Models for Logistics Hazard Identification in Industrial Scenarios

arXiv:2609.09790v1 Announce Type: cross Abstract: Large Multimodal Models (LMMs) large-scale deployment in industrial warehouse settings specifically necessitates that models exhibit human-expert-leve

Multi-Functional Embedding Models for Funder Name Disambiguation in Scientific Publication Records

arXiv:2609.09984v1 Announce Type: new Abstract: Understanding the historical allocation and distribution of research funding advances our knowledge of how scientific research is supported across field

Research

Noise Adaptive Streaming Audio-Visual Speech Token Enhancement for Robust Full-Duplex Spoken Dialogue Models

arXiv:2609.08390v1 Announce Type: cross Abstract: Full-duplex spoken dialogue systems enable simultaneous listening and speaking, but their audio-only perception often fails under background noise and

researcharxiv-cs-ai

Quality Metrics for LLM-Generated Asset Administration Shells: A Perturbation-Based Evaluation Approach

arXiv:2609.07290v1 Announce Type: cross Abstract: The rapid digital transformation of manufacturing, often referred to as Industry 4.0, relies on seamless interoperability between physical and softwar

Qwen-Audio-3.0-ASR Technical Report

arXiv:2609.07549v2 Announce Type: replace Abstract: In recent years, automatic speech recognition (ASR) has witnessed transformative advancements driven by three complementary paradigms: data scaling,

RAP: Research Attention Prediction Reveals Target-Conditioned Evidence Acquisition Biases

arXiv:2609.10092v1 Announce Type: cross Abstract: Large language models (LLMs) increasingly act as research agents, yet their ability to track shifts in research attention is difficult to evaluate bec

Safety boundary maintenance in consumer AI systems responding to pediatric health queries: a cross-platform benchmark evaluation under naturalistic and adversarially pressured conditions

arXiv:2601.09721v2 Announce Type: replace-cross Abstract: Consumer artificial intelligence chatbots are now accessed by hundreds of millions of users seeking health information, yet systematic evaluat

Scratchy: Visual-Scratchpad Multimodal Reasoning for Cryptographic Proof Generation in EasyCrypt

arXiv:2609.06226v1 Announce Type: cross Abstract: Large language models (LLMs) have recently made substantial progress in formal proof generation, yet presenting distinctive challenges in cryptographi

The Failure Happens Before the Drift: The Social Dynamics of Values in LLM Agent Societies

arXiv:2609.05514v1 Announce Type: new Abstract: Large Language Model (LLM)-based agents are increasingly used as proxies for human participants in social science research, yet it remains unclear wheth