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natural language processing

9,261 papers

#natural language process... Preprint Sep 2026

Finding Common Ground: Graded Communal Knowledge in Bluesky Starter Packs

Communication is made possible by common ground---the unspoken knowledge that people share and presuppose of one another, whether that be online or offline. In his conception of common ground, Clark (1996) distinguishes between personal and communal common ground, and asserts that the latter is graded: the more communi...

Sagar Kumar, L. Prince, Julia Mendelsohn et al. · 0 citations
#natural language process... Preprint Open access Sep 2026

BurnRiSc: Toward Non-Invasive Burnout Screening in Open Source from Public Repository Signals

Burnout is a chronic occupational syndrome, and open source is close to a worst case for it: maintainers absorb unbounded demand with no manager to reallocate work and no organization to notice decline. The cost is not only personal. Burnout precedes withdrawal, and in projects sustained by a handful of maintainers, on...

Timofey Sanko, Yuan Tian, Mariam Guizani · 0 citations
#natural language process... Preprint Sep 2026

A Cross-Lingual Acoustic Disease-Alignment Framework for Respiratory Health Assessment from Spontaneous Speech

CL-DAF is presented, a Cross-Lingual Disease-Alignment Framework that identifies acoustic dimensions whose disease effects remain consistent across languages and provides a foundation for multilingual clinical speech models emphasizing pathology over language-dependent variation.

Roksana Khanom, Raghib Asfak Tasnim, Bodrun Nahar Bithi et al. · 0 citations
#natural language process... Preprint Sep 2026

CovR: Coverage-Aware Hardware Verification via Reasoning-Guided Reinforcement Learning

CovR is presented, an agentic framework for automated testbench generation that combines self-reflection loops with simulation-based feedback to maximize coverage and a reinforcement learning (RL) framework tailored for coverage-driven testbench generation, leveraging tool-derived rewards from simulation and coverage f...

Manar Abdelatty, Maryam Nouh, Sherief Reda · 0 citations
#natural language process... Preprint Sep 2026

Unifying Models of Intergroup Hostility in Online Discourse

Hostile rhetoric toward social groups can normalize exclusion and justify mistreatment, as well as contribute to rising polarization and political violence. Efforts to moderate hostile rhetoric in online speech draw on foundational theories in social and moral psychology, and political science. However, these theories...

Patrick Gérard, Julia Mendelsohn, Kristina Lerman · 0 citations
#natural language process... Preprint Sep 2026

JEPA-Anything: Learning Predictive Models across Different Worlds

JEPA-Anything, a domain-agnostic framework based on orthogonal predictive factorization (OPF), achieves the lowest one-step and 100-step molecular errors among compared methods in all four systems and supports a common factorized predictive principle across heterogeneous worlds.

Tao-Yong Cui, Zhong-Yao Wang, Xin-Yue Xu et al. · 2 citations
#natural language process... Preprint Sep 2026

On-Demand Attention: Language Models Know When to Recall

These findings show that pretrained decoding states can support both token prediction and decisions about accessing distant information, allowing models to allocate global computation as needed during decoding, allowing models to allocate global computation as needed during decoding.

Hai-Bo Feng, Ruiqi Liang, Dong-Yang Jin et al. · 0 citations
#natural language process... Preprint Open access Sep 2026

Summarization Bias: The Directional Collapse of Objective Projection into Told-Mode Labels in Large Language Models --- A Conceptual Framework and Registered Test Protocol

This paper introduces and operationalizes summarization bias: a proposed systematic tendency of large language models (LLMs) to represent narrative meaning as an abstract summary label rather than as the reconstructable inferential structure that produces it. Within the Bulut Doctrine, narrative effect is theorized alo...

Levent Bulut · 0 citations
#natural language process... Preprint Sep 2026

HerHealthEval: Evaluating Multilingual and Register-Sensitive Understanding of Women's Health Communication

These findings show that robust multilingual healthcare evaluation requires explicit testing of register variation, uncertainty handling, and the provenance and invariance of adaptation labels.

Hassan Saeed Hassan Albattra, Mazen Bahgat, Rahatara Ferdousi et al. · 0 citations
#natural language process... Preprint Sep 2026

UniPolicy: Unified Objective-Specific Policies for Generative Search Advertising

Search advertising connects user intent with commercial content and plays a critical role in platform monetization. Recent systems typically align pretrained generative models with a single business reward, such as eCPM, or use naive reward fusion for preliminary multi-objective alignment. However, an ideal search adve...

Kun Yao, Yu-Hang Zhou, Yi-Chi Zhang et al. · 0 citations
#natural language process... Preprint Sep 2026

What Does Privileged Information Add to On-Policy Self-Distillation?

AMPLE-Math, a reusable suite of 5,319 mathematical problems with six reasoning views that share the same answer, is constructed and AMPLE-Math, a reusable suite of 5,319 mathematical problems with six reasoning views that share the same answer, is compared, suggesting that OPSD can improve access to existing reasoning...

XiuYu Zhang, Wei Chow, Jun-Feng Fang et al. · 3 citations

From tech blogs

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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.

MIT News · Artificial Intelligence Oct 15, 2026

AI model decodes the language cells use to communicate

A new computational approach reveals how cells communicate to assemble into tissues. This could accelerate stem cell engineering, improve disease models, and inform therapies.

Microsoft Research Blog Oct 15, 2026

Proof-based general-purpose computing with Magnetar

Zero-knowledge proofs can verify computing results without rerunning workloads or exposing sensitive data. Magnetar helps bring them into the mainstream with support for standard programming languages, major speed gains, and quantum-resistant security. The post Proof-based general-purpose computing with Magnetar appeared first on Microsoft Research.

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