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natural language processing

9,261 papers

#natural language process... Preprint Open access Nov 2026

Growing One's AI Tools: A Paradigm of Practice-Grown Tools

Professionals have long used software built for them by others. This article reports the growth of a professional computer-assisted interpreting (CAI) tool built by its own user, a conference interpreter without programming training. Drawing on an eight-week version-controlled record with telemetry from 133 logged sess...

Zeming Zhao · 0 citations
#artificial intelligence Preprint Open access Nov 2026

Reconciling Privacy with Provenance for Language Model Watermarks

Watermarking has great potential for regulating the use of language models (LMs), but its deployment has been marred by controversy, as many users argue that fine-grained tracking of LM usage violates their privacy. This tension reduces the effectiveness of watermarks, as users engage in evasion strategies such as para...

Elise L. Han, Tatsunori Hashimoto · 0 citations
#computer vision Preprint Open access Nov 2026

SVGFaith: A Two-Layer Meta-Evaluation of Faithfulness Metrics for Text-to-SVG Generation

Text-to-SVG systems are commonly evaluated by applying raster-image metrics to rasterised outputs, yet whether these scores capture fine-grained prompt faithfulness remains unclear. We introduce SVGFaith, a two-layer meta-evaluation framework in which the more faithful candidate of each pair is determined by constructi...

Guotao Liang, Haitao Zhou, Biao Liu et al. · 0 citations
#machine learning Preprint Open access Nov 2026

Who Pays for the Knowledge Models Copy? Model Collapse as Rogers' Paradox

Generative models trained on the output of earlier models lose knowledge across generations, rare knowledge first. The remedies that work all bring in information from outside the loop, and the theory of model collapse treats that supply as given: a fixed archive, drawn from a fixed distribution. We argue that the supp...

Nam H. Le · 0 citations
#machine learning Preprint Open access Nov 2026

How Far Can You Steer? Behavior-Capability Frontiers in Contrastive Activation Addition

Activation steering can modify language-model behavior without parameter updates, but behavioral efficacy alone does not determine whether an intervention is usable. Contrastive Activation Addition (CAA) steers targeted behaviors using activation directions derived from contrasting examples, potentially degrading unrel...

Deepanshu Raj · 0 citations
#machine learning Preprint Open access Nov 2026

On the Design of Hyper-Connections: Simplification, Stability, and Scalability

Hyper-Connections (HC) architectures are increasingly adopted in frontier language models, yet their components remain insufficiently understood and introduce non-negligible training overhead. In this work, we systematically study the HC architecture to understand its components and identify simpler, more efficient des...

Xiangdong Zhang, Xiaohan Qin, Sunan Zou et al. · 0 citations
#natural language process... Preprint Open access Nov 2026

Robots in the City: Persona-Based Perceptions of Urban Robots

Pedestrians increasingly encounter robots in urban public spaces without interacting with them, but how robots change the perceived safety of a street remains unclear. We examine how robot presence and type affect perceived safety across urban contexts. We generate 18 images of Seoul streets that vary in time of day, r...

Keonhee Jang, Kanghoon Lee, Seokwoo Yun et al. · 0 citations
#computer vision Preprint Nov 2026

Modality-Aware Expert Pruning for MoE-Based Multimodal Large Language Models

Experiments show that MAEP outperforms modality-agnostic baselines on the majority of multimodal benchmarks while remaining competitive on text-only tasks, and reducing the BF16 expert weight footprint by about 27 GB so that the full weight footprint of an approximately 58 GB model fits within a single 40 GB GPU.

Donggeun Kim · 0 citations
#artificial intelligence Preprint Open access Nov 2026

Routes of Reasoning: Reading and Reshaping Test-Time Compute in MoE Models

Reasoning models allocate test-time compute across distinct behaviors such as planning, deriving, and verifying. However, models frequently "overthink," continuing to verify and re-derive long after finding a correct answer. This wastes expensive compute and can even degrade performance. Existing interventions, such as...

Shengjie Wang, Mohsen Fayyaz, Nanyun Peng · 0 citations
#artificial intelligence Preprint Open access Nov 2026

Autonomous agents for electricity-system planning

Planning electricity systems requires repeated decisions that connect regional resources, investment, operation and network constraints. Here we present an autonomous planning framework that carries prepared regional scenarios through proposal, numerical evaluation, feedback interpretation, redesign and final plan sele...

Yoon Pyo Lee, Samrendra Roy, Jay Phil Yoo et al. · 0 citations
#artificial intelligence Preprint Open access Nov 2026

PAYWORTHY: Can LLMs Predict Which Freelance Jobs an AI Agent Will Complete?

Before an AI agent takes on a paid job, someone has to judge whether it is likely to succeed. We test whether frontier language models can make this call before any attempt. We propose PAYWORTHY which contains 1{,}494 real freelance job postings, sampled from 18.8M postings made between 2020 and 2026 on a freelancing p...

Mohammad Reza Rezaei, Dingxian Wang, Brett Levert et al. · 0 citations
#artificial intelligence Preprint Open access Nov 2026

Text-Only Domain Adaptation for Low-Resource Medical ASR: Shallow Fusion and Density Ratio Rescoring for Hausa

Automatic speech recognition (ASR) systems often struggle with specialised medical vocabulary, especially in low-resource languages where domain-specific speech data are scarce. We investigate text-only domain adaptation for Hausa medical ASR using the fixed MMS-1B-FL102 acoustic model and two decoding-time language-mo...

Oche David Ankeli, Hassan Adelani Luqman, Theodora Ngozi Egbunike et al. · 0 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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