All Articles
17879 articles total
LCG: Long-Context Consistent Image Generation with Sparse Relational Attention
Introduction of LCG, a framework for long-context multi-image generation using Sparse Relational Attention and a new consistency dataset.
KG-TRACE: A Neuro-Symbolic Framework for Mechanistic Grounding in Antimicrobial Resistance Prediction
Introduction of KG-TRACE, a neuro-symbolic framework for grounding antimicrobial resistance predictions in biological knowledge graphs.
My Steam Machine Is a 50ft HDMI Cable
A discussion on a unconventional Steam Machine setup using a very long HDMI cable for remote hardware placement.
Low Resource Multimodal Translation of Nepali Spoken Words into Emotion-Conditioned Sign Language Avatars
Introduction of NEST-V1, a lightweight multimodal framework for translating spoken Nepali words into emotion-conditioned sign language avatars for edge deployment.
Generative AI and Copyright Infringement: A Legal-Technical Analysis of AI Music Generation Systems Under 17 U.S.C. Title 17
A legal-technical analysis of AI-generated music and the regulatory gaps regarding synthesized vocal likeness under US copyright law.
From Lexicon to AI: A Structured-Data Pipeline for Specialized Conversational Systems in Low-Resource Languages
A methodology for creating specialized conversational AI for low-resource languages by transforming WordNet lexicons into instruction-response pairs, using 4-bit quantization and LoRA.
Dream machine -- the next creative economy
An analysis of the structural transformation of creative industries due to GenAI, introducing the 'slop ceiling' and the Human-AI Agency Continuum.
A Multi-Layer AI Framework for Information Landscape Analysis
Proposed multi-layer AI framework for analyzing the informational landscape to detect misinformation through epistemic mapping rather than binary fact-checking.
Divergent Recommendations, Convergent Diagnoses: Cross-Provider Failure-Mode Convergence in AI Commercial Recommendation
Research on how different LLM providers (ChatGPT and Claude) diverge in recommendations but converge on failure-mode diagnoses for brand visibility.
The Governance Inversion Hypothesis: Why More AI Regulation May Produce Less Organisational Control
The Governance Inversion Hypothesis suggests that increased AI regulation may actually decrease operational control over AI systems due to procedural density.
The Open Source Economic Index of AI Adoption and Capability
Development of an open-source economic index to measure AI adoption and capability across occupations using user-LLM chat data and MCP servers.
Dot-Flik: A Scalable Edge AI Architecture for Distributed Insect Monitoring
Dot-Flik, a scalable edge AI architecture for distributed insect monitoring using a motion-informed frame filtering algorithm to reduce data processing costs.
Trump Mobile will take your $499 right now
Trump Mobile's T1 Phone is now available for general purchase at $499, moving beyond the initial deposit-only preorder phase.
When Does Combining Language Models Help? A Co-Failure Ceiling on Routing, Voting, and Mixture-of-Agents Across 67 Frontier Models
Researchers identify a 'co-failure ceiling' in multi-model LLM systems, showing that accuracy gains from routing or voting are limited by the rate at which all models fail on the same query.
Language-Based Digital Twins for Elderly Cognitive Assistance
A new language-based digital twin framework uses LLMs and cVAEs to mimic elderly conversational behavior for non-invasive monitoring of Mild Cognitive Impairment.
Benchmarking Open-Weight Foundation Models for Global AI Technical Governance
A benchmark study reveals geographic bias in open-weight foundation models, finding that LLMs are significantly less accurate for underrepresented countries.
Know2Guess: A Contamination-Aware Multi-Zone Benchmark for Knowledge-Boundary Evaluation in Large Language Models
The Know2Guess benchmark provides a protocol to distinguish between an LLM's supported knowledge and unsupported guessing, accounting for data contamination.
Helpfulness Hurts: Domain-Dependent Degradation of Mid-Trained Compassion Values Under Post-Training
Research indicates that 'helpfulness' post-training in LLMs can inadvertently degrade animal compassion values instilled during mid-training.
Investigating LLM's Problem Solving Capability -- a Study on Statics Questions
A study on mechanical engineering statics problems finds that LLM accuracy drops significantly when diagrams are introduced and multi-step reasoning is required.
Assert, don't describe: Linguistic features that shift LLM reasoning about animal welfare
Analysis shows that assertive language and explicit moral vocabulary in training data shift LLMs toward stronger pro-animal-welfare reasoning more effectively than neutral descriptions.