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natural language processing

9,568 papers

#artificial intelligence Preprint Aug 2026

ABAI at COLIEE 2026 Task 1: Multi-Stage Retrieval with GraphRAG-Enhanced Meta-Learning, and a Post-Hoc Study of the Cross-Validation-to-Test Gap

The ABAI submission to COLIEE 2026 Task 1, case law retrieval is presented, together with a controlled study of why it underperformed, and four evaluation artifacts are document, each of which reversed a result once the protocol was corrected.

Minhan Cho, Soyoung Park, Daejin Choi et al. · 0 citations
#artificial intelligence Preprint Aug 2026

WatchPoint: Executable User Feedback for Real-World Agentic Web Development

WatchPoint is introduced, a simulated-user system that mimics real developer behavior by generating and executing diagnostic scripts against the running application, producing structured observations that guide the coding model's retry and identifies a pattern of capability gaps that governs when simulated-user feedbac...

Guanqun Yang, Wei Yang, Xueqing Liu · 0 citations
#artificial intelligence Conference Open access Mar 2026

Dynamic Deep Prompt Optimization for Defending Against Jailbreak Attacks on LLMs

Experiments demonstrate that DDPO significantly outperforms static prompt optimization methods, particularly on weakly aligned models and when handling semantically ambiguous benign prompts, successfully distinguishing them from genuinely harmful requests.

Doniyorkhon Obidov, H. Yu, Xiaolong Guo et al. · 4 citations
#artificial intelligence Preprint Aug 2026

TSS: Target-Side Sparsification for Speculative Decoding in Domain-Specific Large Language Models

TSS, a target-side sparsification framework for speculative decoding that employs an acceptance- and metric-aware breadth search to explore multi-layer skip configurations without imposing a fixed priority between the two objectives, is proposed.

Hai-Bo Hu, Lian-Ming Huang, Qiao Li et al. · 0 citations
#artificial intelligence Preprint Open access Sep 2026

Syndrome, Synergy, and Safety: Structured Reasoning and Knowledge-Driven Alignment for TCM Prescription Generation

Applying large language models to Traditional Chinese Medicine (TCM) prescription generation reveals three clinically critical gaps: models produce end-to-end mappings without auditable reasoning following the li-fa-fang-yao paradigm (SR Gap), treat each encounter in isolation without follow-up adjustment via sui zheng...

Zheng Chen, ZhiCheng Du, Haoxuan Li et al. · 0 citations
#artificial intelligence Preprint Sep 2026

Slow Decay and Silenced Expression: Iterated Subliminal Trait Transfer in Language-Model Lineages

Language models are increasingly trained on the outputs of other models, forming chains that the authors call lineages, in which a trait present in one generation can pass to the next, and whether such a trait holds or fades across lineages is studied.

Ryan Vo, Duc-Vu Nguyen, Matt Kretchmar et al. · 0 citations
#artificial intelligence Open access Sep 2026

Compressing Long Context into Answer-Aligned Memory Embeddings for LLM Inference

A Context-to-Answer-Aligned Memory Compression (CMC) framework is proposed, which compresses long input contexts into compact Context Memory Embeddings aligned to any frozen decoder's embedding space, reducing inference costs without modifying decoder weights.

Md. Mostafizer Rahman, Md. Faizul Ibne Amin, Md. Shahajada Mia et al. · 1 citation
#artificial intelligence Preprint Open access Sep 2026

Universal Fractal Natural Language Decision Map: Real-Time Edge Triage Across Heterogeneous Domains

Deploying Large Language Models for runtime operational triage incurs prohibitive latency (>100-500 ms), high VRAM requirements (>4-8 GB), and excessive energy dissipation. Extending Mandelbrot Fractal Neural Synthesis (Dagli et al., 2026), this paper presents the Universal Fractal Natural Language Decision Map, realiz...

Volkan Da\u{g}l{\i}, Zerrin Da\u{g}l{\i}, Da\u{g}han Da\u{g}l{\i} · 0 citations
#artificial intelligence Book Open access Sep 2026

Passes Alone, Fails Together: Benchmarking Semantic Coordination in Parallel LLM-Agent Development

This work studies parallel coding agents' failures with stale, a benchmark for semantic coordination, and finds that among 834 runs on 417 mined Django pairs, only one showed interference after correcting the grading procedure.

Hao-Chen Xia, Eugene Wu, Yongjoo Park · 0 citations
#artificial intelligence Preprint Sep 2026

Trains but Doesn't Learn: A Post-Training Delivery Benchmark for LLM Agents as Forward-Deployed Engineers

This work ran four frontier agents end to end end to end on metered L40S, A100, and H200 GPUs across 8B to 70B open bases, certifying every scenario before scoring, and ran a human FDE arm under the same oracle and compare every agent against it.

Wei-Hang Ding, Jun-Fei Zhan · 0 citations
#artificial intelligence Review Open access Jul 2026

From Pattern Recognizers to Personalized Companions: A Survey of Large Language Models in Mental Health

Viewing the field through this developmental lens, this survey provides a comprehensive synthesis of existing work, an insightful narrative of its trajectory, and a clear roadmap for future innovation in responsible, effective, and human-centered AI for mental healthcare.

He Hu, Yucheng Zhou, Qianning Wang et al. · 4 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.

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