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natural language processing

9,568 papers

#artificial intelligence Preprint Oct 2026

Cooperation Without Adaptation: LLM Agents in a Collective-Risk Dilemma

Language-model agents are increasingly deployed to act on behalf of people in settings where individual decisions shape shared outcomes. We examine whether five production models adapt their contributions to changing risks and partner behaviour, or instead follow a relatively fixed strategy. In a collective-risk dilemm...

Trung-Kiet Huynh, Dao-Sy Duy-Minh, Chi-Nguyen Tran et al. · 0 citations
#natural language process... Preprint Open access Oct 2026

Too Emotional to Be Fake? Intra-Utterance Emotion Shifts Expose Failure Modes in Speech Deepfake Detectors

Expressive speech synthesis can now change emotion within a single utterance, yet its impact on deepfake detection remains unclear. We introduce EmoShift, a benchmark comparing emotion-stable (AA) and emotion-changing (AB) speech to examine these effects while accounting for static emotion identity and acoustic confoun...

Jingyi Chen, Surya Koppisetti · 0 citations
#natural language process... Preprint Oct 2026

Veil-Then-Reveal: Protecting PII Privacy via Reversible Pseudo-Anonymization in Zero-Trust User--LLM Interaction

Large language models (LLMs) increasingly process sensitive documents and personal information, yet sending prompts containing personally identifiable information (PII) to remote providers exposes data subjects and organizations to risks from logging, retention, model training, and unintended disclosure. Existing anony...

Mohamed Elmahallawy, M. Shaaban, Thomas E. Carroll · 0 citations
#natural language process... Preprint Open access Oct 2026

A misinformation playbook sharpens judgement without breeding cynicism

Misinformation harms public health and democracy, and generative artificial intelligence now writes falsehoods as persuasive as people's. Defences range from fact-checking individual claims to training people to resist falsehoods. Yet many claims are too new to check, and interventions that teach doubt can reduce belie...

Tong Guo, Teng Ye, Yutong Xie et al. · 0 citations
#natural language process... Preprint Open access Oct 2026

Risk and Refusal: Mechanisms of LLM Responses to Suicidal Ideation

Refusal is a common safety mechanism in large language models (LLMs), yet in contexts of suicidal ideation (SI), refusing to engage can itself constitute a safety failure. We evaluate how eight instruction-tuned LLMs respond to SI and self-harm disclosures across three datasets, varying whether models are informed that...

Drishti Goel, Soorya Ram Shimgekar, Jeongah Lee et al. · 0 citations
#artificial intelligence Preprint Open access Oct 2026

GlobeBench: Evaluating Text-Based World Model Capabilities for Scalable Environment Simulations

Text-based world models have recently shown potential to simulate complex RL environment state transitions for a diverse set of use cases. However, no standardized benchmark exists to compare, study and improve these models. Through this paper, we attempt to solve this problem by building GlobeBench, a novel benchmark...

Nicholas Saban, Charvi Bannur, Mariya Vasileva et al. · 0 citations
#artificial intelligence Preprint Open access Oct 2026

Not All Graphs Are Maps: A Task-Agnostic Exploration Framework for Mobile GUI Navigation

Modern mobile GUI agents can perceive visible screens and execute local actions, but they still lack persistent app-specific navigation knowledge: where functions live, which pages contain them, and which screens are equivalent across repeated visits. We introduce TAG-Nav, a Task-Agnostic Graph Navigation framework tha...

Adamo Orsini, Seyed Mehdi Ayyoubzadeh, Sadman Rakib Pinon et al. · 0 citations
#natural language process... Preprint Oct 2026

Exploring The Empirical Privacy Landscape of Synthetic Data

Methods for training language models on sensitive data differ in how they balance capability gains against the risk of leaking private information. In this paper, we present a controlled comparison of data-level and training-level interventions for navigating the capability-privacy tradeoff on synthetic medical records...

Zihao Zhao, Avi Schwarzschild, Casey Meehan et al. · 0 citations
#artificial intelligence Preprint Oct 2026

Repairing LLM-Generated Specifications with Deterministic Diagnosis

Large language models (LLMs) are increasingly used as formalizers: given a reasoning problem expressed in natural language, they produce a formal specification that a symbolic solver can then solve, with guarantees relative to that specification. Many specifications are runnable yet semantically wrong, encoding incorre...

G. Vaccarino, Emanuele La Malfa, De-Hai Min et al. · 0 citations
#artificial intelligence Preprint Open access Oct 2026

Are Large Reasoning Models Good Everyday Reasoners? A Comparison with Non-Reasoning Models on Logical Reasoning Tasks

Large reasoning models (LRMs) that leverage test-time computation achieve strong performance on mathematical and scientific benchmarks and are increasingly deployed in real-world applications. However, their ability to perform \textit{everyday logical reasoning}, which often departs from textbook formal logic, remains...

Kentaro Ozeki, Risako Ando, Takanobu Morishita et al. · 0 citations
#natural language process... Preprint Oct 2026

High prevalence of antagonizing rhetoric in trending topics on Twitter/X

Disagreement between political opponents is a central element of democracy. This disagreement can be voiced in different ways. An opponent can be antagonized, i.e. portrayed as an enemy that needs to be overcome, or they can be criticized, i.e. treated as a legitimate adversary with whom one can engage. While the latte...

A. Pournaki, E. Olbrich · 0 citations
#artificial intelligence Review Oct 2026

PRIME: Towards Verifiable Evidence-Grounded Reasoning in LLM Agents

LLM agents are used to check records against an organization's requirements, for example whether a vulnerability report is ready for investigation. Requirements often allow several ways to be met, such as a severity rating with a curator-reviewed advisory or a published advisory link. Agents fail by accepting a report...

Hamed Khosravi, Xiao-Ming Huo · 0 citations

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Microsoft Research Blog Oct 22, 2026

Flint-interactive: A language for creating interactive data visualizations

Flint-interactive gives AI agents a language for creating interactive visualizations. Click a chart, filter data, highlight related content, and explore beyond the view the author originally chose. The post Flint-interactive: A language for creating interactive data visualizations appeared first on Microsoft Research.

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