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natural language processing

9,261 papers

#artificial intelligence Preprint Open access Oct 2026

Entity Matching using Decision Models

Entity matching is the task of deciding whether two records describe the same real-world entity. Current entity matching methods rely on pre-trained language models (PLMs) which require task specific fine-tuning or generative large language models (LLMs) which do not require task-specific fine-tuning but are slow and e...

Aaron Steiner, Ralph Peeters, Christian Bizer · 0 citations
#natural language process... Preprint Open access Oct 2026

Does the Outfit Change the Price? Context Halo in Vision-Language Model Valuation of an Identical Low-Cost Necklace

A chunky gold-tone chain necklace bought online for 2.43 USD was photographed four ways: worn with formal attire against a wood-panelled wall, worn at a party, worn with casual clothing in a recycling yard, and laid flat with no person present. We asked six frontier language models to estimate its price in 1,164 indepe...

Brianne Lee · 0 citations
#artificial intelligence Preprint Open access Oct 2026

HARP-LoRA: Hierarchy-Conditioned Rank Projection for Low-Rank Adaptation in Scientific Table Understanding

Tabular data is widely used in scientific applications, where complex layouts, including multi-level headers, merged cells, captions, and footnotes, make information extraction difficult. This is particularly important in pharmacokinetics (PK), where values must be correctly associated with the drug, species, dose, adm...

Hossein Sholehrasa, Mohammadhossein Amini, Doina Caragea et al. · 0 citations
#artificial intelligence Review Oct 2026

Large Language Models: A Plain-Language Overview for Engineers

The article starts with the Transformer, which connects words in context, and pre-training, where models learn to predict text, and explains how fine-tuning adapts models to requests, with reinforcement learning from human feedback using human answer rankings.

Bahaeddin Turkoglu · 0 citations
#natural language process... Preprint Open access Oct 2026

RefinedGAW: A Refined German Academic Web Dataset

The largest open German text datasets are built from broad web crawls, which provide scale but limited coverage of specific domains. We introduce RefinedGAW, a processed and annotated resource derived from 26 semi-annual crawls of the German Academic Web, totaling 122 million documents and 314 billion tokens, with full...

Maximilian Idahl, Oleh Astappiev, Benedikt Droste et al. · 0 citations
#natural language process... Preprint Open access Oct 2026

STEP: Soft Trajectory Estimation of Prediction Correctness via Per-Step Probability Scoring

Estimating the correctness of large language model (LLM) predictions without access to ground truth is critical for reliable deployment in high-stakes settings. Existing approaches, such as entropy and perplexity, operate solely on final output statistics, discarding the rich information encoded in intermediate reasoni...

Chenyang Yu, Zifan Zeng, Qunli Zhang et al. · 0 citations
#artificial intelligence Preprint Open access Oct 2026

The Price of Scale in Proactive Memory Recall

A long-lived assistant that brings up memories without being asked must decide at every turn whether anything in its store is worth an interruption. We show that this decision is a multiple-testing problem whose difficulty grows with the store size $N$. On streaming replays of LongMemEval and LoCoMo, a similarity thres...

Yichuan Chen, Xin Wang · 0 citations
#natural language process... Preprint Open access Oct 2026

Does the Voynich Manuscript Mean Anything? Calibrated Tests Find Little Trace of Language

The Voynich manuscript is a fifteenth-century book in a script that no one can read. One account holds that its text means nothing and that a scribe made it by copying his own words and changing them a little. The other holds that a real language lies hidden behind a cipher. We write each account as a program that fill...

Xin Zhang, Victor S. Sheng · 0 citations
#artificial intelligence Preprint Open access Oct 2026

Efficient Proof Generation for Lean Statements with Multiple Candidate Answers

In formal systems such as Lean 4, efficiently finding answers to mathematical problems and generating verifiable proofs is an important task in automated mathematical reasoning. In the traditional way where an upstream solver provides multiple candidate answers, the common workflow requires searching for proofs for eac...

Pengzhen Lin, Ke Zhang, Maziar Raissi et al. · 0 citations
#natural language process... Preprint Open access Oct 2026

Beyond the Opening: Tracing the First Token's Persistent Influence on Reasoning Length

Understanding how individual token choices affect reasoning length is important for characterizing reasoning models. Building on prior findings that changing the first reasoning token (hereafter, the first token) can substantially alter reasoning length, we focus on this initial choice to investigate how its influence...

Ruochen Liu, Hao Yan, Ziluowen Luo et al. · 0 citations
#artificial intelligence Preprint Open access Oct 2026

Xing USP: A Cross-Family Semantic Contract for Information Extraction and Intent-Slot Parsing

Structured semantic parsing is typically judged by whether the correct category is assigned, which leaves value recovery and instance-level associations unexamined: a system may recognize an event yet bind an argument to the wrong instance, or identify an intent yet supply an incorrect slot value. We present USP, a cro...

Zhongqiu Li, Boyang Wang, Ruiyu Fang et al. · 0 citations
#artificial intelligence Preprint Open access Oct 2026

Improving the Chain-of-Thought Compressibility of Pruned Reasoning Models via Long--Short Contrastive Pruning

Large reasoning models are costly to serve because they are large and because they generate long chains of thought (CoT). Weight pruning and CoT compression address these two costs separately, but they interfere in that pruning adds redundant reasoning on problems the model still solves and incomplete reasoning on thos...

Tao Jing, Chen Kang, Feifei Zhai et al. · 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.

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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