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natural language processing

9,568 papers

#artificial intelligence Preprint Open access Oct 2026

SignVerse-2M: A Two-Million-Clip Pose-Native Universe of 55+ Sign Languages

Large-scale sign language resources usually pair RGB videos with text and support recognition, translation, and generation. However, RGB frames contain backgrounds, clothing, and other appearance information unrelated to signing motion. Representing the videos as whole-body keypoints such as DWPose removes much of this...

Sen Fang, Hongbin Zhong, Yanxin Zhang et al. · 0 citations
#artificial intelligence Preprint Open access Oct 2026

Do Compact SSL Backbones Matter for Audio Deepfake Detection? A Controlled Study with RAPTOR

Self-supervised learning (SSL) underpins modern audio deepfake detection, yet most prior work centers on a single large wav2vec2-XLSR backbone, leaving compact under studied. We present RAPTOR, Representation Aware Pairwise-gated Transformer for Out-of-domain Recognition a controlled study of compact SSL backbones from...

Ajinkya Kulkarni, Sandipana Dowerah, Atharva Kulkarni et al. · 0 citations
#machine learning Preprint Open access Oct 2026

Improving the Performance of Compressed Transformers with Post-Hoc Embedding Alignment

Model compression is necessary for deployment of transformer models in resource-constrained environments. However, compression reduces the performance of transformer models on downstream tasks. Existing solutions such as Knowledge Distillation (KD) and Parameter Efficient Fine-Tuning (PEFT) have their own limitations....

Rohit Raj Rai, Abhishek Dhaka, Amit Awekar · 0 citations
#artificial intelligence Preprint Open access Oct 2026

GraphDancer: Training LLMs to Explore and Reason over Graphs via Curriculum Reinforcement Learning

Large language models (LLMs) increasingly rely on external knowledge to improve factuality, yet many knowledge sources on the Web, such as scholarly indexes and product catalogs, are organized as heterogeneous graphs. Reasoning over such graph-structured knowledge poses two key challenges: (1) navigating structured, sc...

Yuyang Bai, Zhuofeng Li, Ping Nie et al. · 0 citations
#machine learning Preprint Open access Oct 2026

Fast KVzip: Efficient and Accurate LLM Inference with Gated KV Eviction

Efficient key-value (KV) cache management is crucial for the practical deployment of large language models (LLMs), yet existing compression techniques often incur a trade-off between performance degradation and computational overhead. We propose a novel gating-based KV cache eviction method for frozen-weight LLMs that...

Jang-Hyun Kim, Dongyoon Han, Sangdoo Yun · 0 citations
#artificial intelligence Preprint Open access Oct 2026

Navigating Ideation Space: Decomposed Conceptual Representations for Positioning Scientific Ideas

Scientific discovery requires new ideas to be situated within an ever-expanding landscape of existing knowledge. An emerging challenge is how to identify conceptually relevant prior work from rapidly growing literature, and assess how a new idea differentiates from existing research. Current embedding approaches typica...

Minqian Liu, Yuexi Shen, Dawei Zhou et al. · 0 citations
#natural language process... Preprint Open access Oct 2026

Automotive-ENV: Benchmarking Multimodal Models in Automotive Cockpit Environments

Multimodal models have demonstrated strong capabilities in web, desktop, and mobile GUI environments, but their performance in automotive cockpit systems remains largely unexplored. In-vehicle GUIs introduce unique challenges beyond traditional GUI interaction, including vehicle-state reasoning, implicit intent underst...

Junfeng Yan, Biao Wu, Meng Fang et al. · 0 citations
#machine learning Preprint Open access Oct 2026

Evolving Language Models without Labels: Majority Drives Selection, Novelty Promotes Variation

Large language models (LLMs) can improve through reinforcement learning with verifiable rewards (RLVR), but many settings lack reference answers or external verifiers. Label-free self-improvement instead constructs training signals from the model's own outputs. Because the same policy generates both the candidate respo...

Yujun Zhou, Zhenwen Liang, Haolin Liu et al. · 0 citations
#computer vision Aug 2025

Can Multi-modal (reasoning) LLMs detect document manipulation?

This study investigates the efficacy of state-of-the-art multi-modal large language models-including OpenAI O1, OpenAI 4o, Gemini Flash (thinking), Deepseek Janus, Grok, Llama 3.2 and 4, Qwen 2 and 2.5 VL, Mistral Pixtral, and Claude detecting fraudulent documents, and reveals that top-performing multi-modal LLMs demon...

Zi-Sheng Liang, Kidus Zewde, R. Singh et al. · 8 citations
#natural language process... Preprint Open access Oct 2026

Training in translation tools and technologies: Findings of the EMT survey 2023

This article reports on the third iteration of a survey of computerized tools and technologies taught as part of postgraduate translation training programmes. While the survey was carried out under the aegis of the EMT Network, more than half of responses are from outside that network. The results show the responsivene...

Andrew Rothwell, Joss Moorkens, Tomas Svoboda · 0 citations
#artificial intelligence Preprint Open access Oct 2026

Artificial Leviathan: Exploring Social Evolution of LLM Agents Through the Lens of Hobbesian Social Contract Theory

The emergence of Large Language Models (LLMs) and advancements in Artificial Intelligence (AI) offer an opportunity for computational social science research at scale. Building upon prior explorations of LLM agent design, our work introduces a simulated agent society where complex social relationships dynamically form...

Gordon Dai, Weijia Zhang, Jinhan Li et al. · 0 citations
#artificial intelligence Preprint Open access Oct 2026

Budgeted Prompt-Set Expansion and Refinement for Language Models via Simulation Optimization

A prompt is an instruction or description provided by the user to guide a generative language model toward outputs that meet application requirements. When these requirements change, existing prompts may need to be adapted and improved. Evaluating candidate prompts requires time and computational resources. We therefor...

Haoting Zhang, Jinghai He, Rhonda Righter 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.

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