Dessn raises $6M for its production focused design tool
A new startup called Dessn has raised $6M to build AI-powered design tools that work directly with production codebases.
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A new startup called Dessn has raised $6M to build AI-powered design tools that work directly with production codebases.
llama.cpp adds llama-eval benchmarking tool supporting AIME, GSM8K, GPQA for local quantized model evaluation.
Been using Claude Code heavily and kept running into the same thing everyone here talks about: the model ignores your rules. You tell it to write tests first, it writes the implementation. You give it coding standards, it cherry-picks which ones to follow. And as your rulebook grows, you're burning more and more tokens stuffing everything into context when only a handful of rules are relevant to what you're working on. So I built Writ. Two pieces: A retrieval engine that picks only the relevant rules and skills for the current task. It runs a five stage pipeline over a Neo4j knowledge graph...
Transfer learning evaluation across 11 pre-trained models for image classification; standard practice study without novel methodology.
Random-Set GNNs introduce uncertainty quantification for graph neural networks via epistemic and aleatoric uncertainty modeling.
Evaluates LLM ability to generate Entity-Relationship diagrams from natural language; identifies systematic limitations in database modeling tasks.
QDSB combines quantization with Schrödinger bridges for generative modeling from unpaired samples; highly specialized technical approach.
Applies Bayesian optimization and DRL to aerodynamic control of high-lift wings; domain-specific application outside AI research scope.
RuDE framework predicts post-training potential of LLMs before fine-tuning; addresses model selection gap using rubric-based evaluation.
RTX 4090 power optimization for llama.cpp: reduce consumption 40% via power limits without performance loss.
Reach-Avoid Probability Certificates (RAPCs) enforce probabilistic safety constraints in stochastic RL while minimizing cost.
Dual Group Advantage Optimization mitigates order bias in LLMs to improve RAG and in-context learning fairness.
Vapi says its enterprise business has grown 10-fold since early 2025 as companies shift customer support and sales calls to AI agents.
Humanoid robot as V2X complement for intersection collision avoidance; autonomous systems application, not frontier AI.
NOFE enables continuous dimensionality reduction via function-to-function mappings using Graph Kernel Operators.
GAN-based stochastic cloud subcolumn generator for Earth System Models improves representation of subgrid cloud variability.
Reddit discussion alleging Anthropic incorporates open-source features (MCPs, memory, goals) without attribution to original developers.
Target-guided dialogue system uses scenario modeling and intent-keyword bridging to steer conversations toward predefined topics.
Google reports hackers using AI to automate computer intrusions, escalating security concerns for enterprise infrastructure.
ClipSum leverages frozen CLIP features with temporal modeling for multimodal abstractive summarization of instructional videos.
Study reveals LLM miscalibration in social science measurement tasks; confidence filtering can bias downstream empirical estimates.
Counterfactual Trace Auditing framework measures how agent skills change LLM behavior via structured Skill Influence Pattern annotations.
Random soft prompts without training reach comparable reasoning accuracy to optimized prompts, suggesting injection itself aids LLM reasoning.
RobustToolBench benchmark exposes tool-use agent failures from deployment noise; domain-randomized RL improves robustness.
StepCodeReasoner supervises intermediate execution traces via RL to prevent reward hacking in code reasoning tasks.
Sparse autoencoders on LLM layer transitions detect out-of-domain interactions without treating model as black box.
STAGE framework addresses semantic drift across modality domains in federated graph learning with multimodal node attributes.
Study quantifies sample efficiency in Predictive Coding vs Backpropagation using target alignment metric, finding PC enables more efficient learning in small-scale experiments.
Claude Haiku vulnerable to multi-turn prompt injection via fictional rule construction and word-filling technique.
Paper formalizes positional encoding requirements for Transformer-based neural combinatorial optimization on vehicle routing, accounting for spatial structure unlike NLP.