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natural language processing

9,568 papers

#machine learning Preprint Oct 2026

BioBigBird: A Sparse Attention Model for Long-Range Dependency Processing in Biomedical Text

While domain-specific Large Language Models (LLMs) have encoded vast biomedical knowledge, their limited context windows often hinder a deep understanding of nuanced relationships within and across texts. To address this limitation, we introduce BioBigBird, a bidirectional language model pre-trained on extensive biomed...

Roshan Balaji, S. Pavan Kumar, Vasudev Gupta et al. · 0 citations
#machine learning Preprint Oct 2026

Phonological Interference in Multilingual Speech Models

Phoneme-level models transcribe or generate speech as a sequence of phonemes, the smallest sound units that distinguish words. These models enable fine-grained pronunciation control and understanding, yet often fail on input that does not match any single training language, such as speech alternating between two langua...

Moran Yanuka, Raja Giryes, Morris Alper · 0 citations
#machine learning Preprint Oct 2026

Selective Listening: Mechanism-Guided Control of Audio Influence in Large Audio-Language Models

Large audio-language models (LALMs) exploit multimodal evidence, yet task-irrelevant audio can alter text-reasoning decisions when listening is unnecessary. Aggregate Accuracy can hide this paired drift because audio-induced repairs and damages may cancel. Paired drift analysis and targeted interventions identify archi...

Yu-Lin Sun, Ke-Le Xu, Yong Dou · 0 citations
#machine learning Preprint Oct 2026

LadderEdit: Edit-Level Residual Compression for Memory-Efficient Lifelong Editing of LLMs

Lifelong editing of LLMs requires storing thousands of edits after acquisition. A widely used family of approaches attaches one LoRA adapter per edit, which preserves behavior but grows linearly in storage. To address this challenge, we propose LadderEdit, a method that compresses each LoRA adapter after it is acquired...

Xiao-Bing Yu, Pei-Jie Qiu, Jin Yang et al. · 0 citations
#machine learning Preprint Open access Oct 2026

Can a System-One LLM Perform Knowledge Tracing When Few or No Learners Are Logged?

Knowledge tracing (KT) models need many logged learners, so a new course or platform starts without a usable model. In LLM-based KT the LLM generates the answer, which we call System-Two; it is either fine-tuned on the target data or reasons and votes over ten samples, which is slow and gives coarse probabilities. We a...

Unggi Lee, Haeun Park · 0 citations
#machine learning Preprint Open access Oct 2026

Lapras: Latent Reasoning for Time Series Language Models

Time Series Language Models (TSLMs) offer a promising path toward time series understanding by reasoning over temporal signals and producing natural language answers and explanations. A common approach is Chain-of-Thought (CoT), which generates step-by-step rationales linking relevant signal patterns to final answers....

Yuliang Chen, Yu Yvonne Wu, Patrick Langer et al. · 0 citations
#machine learning Preprint Open access Oct 2026

AI4Fire: Evaluating Large Language Models on Wildfire Tasks

Large language models (LLMs) are entering wildfire management, where overstated evaluations can cost property and lives. How do they perform on wildfire tasks, with and without grounding? Bare means a model receives the task input alone. Grounded means it also receives one task-specific addition: for smoke detection, a...

Yue Zhao, Xiyang Hu, Zuobin Xiong et al. · 0 citations
#machine learning Preprint Oct 2026

Conversational Voice Aesthetic Model with Reinforcement Learning from Human Listeners

We introduce Conversational Voice Aesthetic Model, a speech large language model for describing the voice aesthetics of real or synthetic speech responses in natural conversational contexts. Given a context and a response speech, CVAM describes salient moments that characterize the voice and predicts nine categorical a...

Xi-Lin Jiang, Shun Zhang, T. Jayashankar et al. · 0 citations
#machine learning Preprint Open access Oct 2026

Long Text to Predictive Features: LLM-Guided Blockwise Feature Engineering via Executable Program Search

Industrial risk-control systems typically rely on structured-data models for efficient prediction, yet substantial valuable information remains embedded in unstructured long text. Extracting this information through manual feature engineering is labor-intensive, while requiring a large language model (LLM) to process e...

Ziming Dai, Dabiao Ma, Ziheng Guo et al. · 0 citations
#machine learning Preprint Oct 2026

SparseDecoding: Decoding-Aware Pruning for Accurate and Efficient LLM Inference

The memory-bound nature of the decoding stage of large language model (LLM) inference incurs significant latency. Layer-wise training-free network pruning approaches guided by the Hessian have been a prominent solution to this problem, as pruning reduces the number of nonzero parameters read from memory during decoding...

Qi-Tong Wang, Xin-Wei Niu, Min Su et al. · 1 citation

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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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