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large language models

2,658 papers

#large language models Review Open access Aug 2026

The Talk That Plays: A Narrative Review of Game Dialogue Systems from ELIZA to Personalized Agents

Dialogue systems---the machinery that lets games and agents converse---moved from Weizenbaum's 1966 ELIZA through the narrative engines of Si's Thespian, Mateas and Stern's Facade, and Cavazza's character-based storytelling, and the virtual humans of Swartout and Traum, to Rieser and Lemon's data-driven methodology, Se...

Zen Revista, 10 GAME · 0 citations
#large language models Open access Aug 2026

Multimodal large language model–assisted workflow for image-dependent very short answer question generation and response grading in neurosurgical residency assessment: development and validation study

Very short answer questions (VSAQs) reduce cueing but require substantial specialist effort to develop and grade, particularly when they involve neuroimaging. We evaluated an expert-supervised workflow using multimodal large language models (LLMs) to generate image-dependent neurosurgical VSAQs and support grading of r...

Ye Yuan, Baoping Zheng, Chengye Yao et al. · 0 citations
#large language models Review Open access Aug 2026

The Talk That Plays: A Narrative Review of Game Dialogue Systems from ELIZA to Personalized Agents

Dialogue systems---the machinery that lets games and agents converse---moved from Weizenbaum's 1966 ELIZA through the narrative engines of Si's Thespian, Mateas and Stern's Facade, and Cavazza's character-based storytelling, and the virtual humans of Swartout and Traum, to Rieser and Lemon's data-driven methodology, Se...

Zen Revista, 10 GAME · 0 citations
#large language models Open access Aug 2026

A Generalizable AI-Enabled Framework for Continuous Competitor Intelligence

Background: Competitive intelligence work is routinely scattered across company websites, press releases, industry publications, patent and funding databases, and news feeds. Most organizations still assemble this picture by hand, in spreadsheets and static slide decks that are out of date the moment they are finished....

Sanvi Agarwal, Melinda B. Chu · 0 citations

Benchmarking the Benchmarks: Evaluating Automated Safety Benchmarks for Small Language Models

A large-scale assessment of the effectiveness and robustness of these automated pipelines is conducted by evaluating five widely used benchmark suites across 26 open-source SLMs under a unified judging rubric, which reveals a capability-safety confound that mixes model capability with apparent safety.

Nyamtulla Shaik, Feng-Jun Li, Bo Luo · 1 citation
#artificial intelligence Open access Aug 2026

SecureXon: Design, Architecture, and Evaluation Methodology for an AI-Augmented Web Reconnaissance and Cybersecurity Threat-Intelligence Platform

The rapid expansion of internet-facing web applications has widened the attack surface available to automated scanners, botnets and malicious actors, while common weaknesses such as misconfigured servers, unpatched software, obsolete transport-layer encryption and missing HTTP security headers continue to be exploited...

Sahil Bagde, Swapnil Meshram, Harish Dange et al. · 0 citations
#large language models Open access Aug 2026

Executable Memory and World Coupling: Code as Cognitive Interface in a Self-Modifying Simulation

【Version note — v3】This version removes all literature citations; the Related Work section now states explicitly that the work is bottom-up and experiment-driven, and that we prefer an explicit statement of independence over a performative reference list. Earlier versions (v1, v2) contain incomplete reference lists a...

Yizhang Hu · 0 citations
#large language models Open access Aug 2026

One Number Sets the Limit of Forecasting ── Each Extra Day Costs 1.5874 Times the Initial Accuracy ── Observe 10 Times More Precisely and You Gain Only 4.98 Days ── [Paper 289]

That a weather forecast cannot reach beyond a certain horizon is due neither to missing equations nor to slow computers. This paper asks what sets the limit──the answer is one number, the error doubling time tau_d. No new mathematical theorem and no new law is claimed. Scope of this paper (scope note): No new mathemati...

Yuuki Yamagishi · 0 citations
#large language models Open access Aug 2026

What Changed the Exponent of a Chain Was Self-Avoidance Alone, and above Four Dimensions That Cost Disappears ── An Error of 2.11% in the Exponent Becomes 29.33% in the Length at N=10^9 ── And 2+2=4 Empties Avoidance of Its Meaning ── [Paper 279]

The spread of a polymer chain is fixed by a power of the number of units N. For a Gaussian chain it is N^1/2, and for a self-avoiding chain N^0.588. This paper asks where that difference comes from and where it disappears──the answer is the count 2+2=4. No new mathematical theorem and no new law is claimed. Scope of th...

Yuuki Yamagishi · 0 citations
#large language models Dataset Open access Aug 2026

Police accountability data: United Kingdom, United States and Australia

Derived, machine-readable datasets on police complaints, stop and search, use of force and deaths following police contact, for the United Kingdom, the United States and Australia. Every figure is computed from official open data by code and published with its source, its period and its denominator attached. No figure...

PoliceComplaint.com · 0 citations
#large language models Open access Aug 2026

Fine-Tuning a Large Multilingual Text-to-Speech Model for Nepali on Consumer Hardware: A Teacher Model for Knowledge Distillation with Speaker Identity Verification

Nepali is a low resource language for speech technology and there is very little open text-to-speech support for it. Most high quality neural TTS models are too large to run in real time on the low end machines that are common in Nepal, and the usual answer to that problem is knowledge distillation, where a large teach...

Yagya Raj Sharma · 0 citations
#large language models Open access Aug 2026

Fine-Tuning a Large Multilingual Text-to-Speech Model for Nepali on Consumer Hardware: A Teacher Model for Knowledge Distillation with Speaker Identity Verification

Nepali is a low resource language for speech technology and there is very little open text-to-speech support for it. Most high quality neural TTS models are too large to run in real time on the low end machines that are common in Nepal, and the usual answer to that problem is knowledge distillation, where a large teach...

Yagya Raj Sharma · 0 citations

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