2731 articles
Web agents over long horizons consume thousands of tokens per step (raw DOM, accessibility trees), degrading context. Signal-Driven Observation (SDO) decouples observation from action: a sub-call reads full DOM but returns only task-relevant elements, re-invoked only when a lightweight signal detector fires (URL transitions, new interactive elements, action failures).
HKJudge is the first sentence-level expert-annotated legal discourse corpus. It contains ~290k sentences and ~6.5M tokens from Hong Kong criminal judgments across all court levels, annotated by legal linguistics experts. Two benchmark tasks: rhetorical role classification (26 categories) and legal element extraction. Evaluation on BERT models, open-source and commercial LLMs.
Study on LLM overgeneralization beyond training data. Authors propose the Piggyback Hypothesis: chat-template tokens propagate finetuned behaviors to out-of-distribution domains. They introduce Token-Regularized Finetuning (TReFT) to mitigate emergent misalignment, achieving 33.5% more reduction than data interleaving on Llama-3.1-8B legal domain finetuning.
UnpredictaBench evaluates LLMs' ability to capture true underlying distributions across 448 problems (statistical distributions, stochastic programs, natural scenarios). The KS@N metric uses the Kolmogorov-Smirnov test. No model exceeds 40% at KS@100, revealing a major gap in distributional sampling capability.
GRASP is a data attribution method that models interactions between training subsets via quadratic geometric penalty, surpassing isolated additive approaches. Evaluated on pretraining-scale tasks, it doubles rank correlation for counterfactual subset fidelity and reduces artifact construction costs by nearly an order of magnitude.
Study of scaling laws for language model pretraining in data-constrained regime. Authors propose MIR (masked-input regularization), an auxiliary next-token prediction loss on randomly masked inputs, and SoftQ, a scaling law coupling model and data size under repeated data. MIR improves validation loss on 72M–1.4B models and equals ~1.3× more unique training data.
PROBE, a multi-stage pipeline, diagnoses 802.11 packet captures by combining deterministic PCAP-to-text normalization, multi-model ensembles, and evidence-grounded reliability scoring (without LLM self-assessment). On 87 enterprise Wi-Fi captures, achieves F1=0.957 vs 0.871 expert baseline, eliminates LLM hallucinations and uncalibrated confidence scores.
Geometric analysis of conditions enabling theft of a transformer's final layer. The author proves perfect copying of the last stage is possible under specific conditions, but hidden layers cannot be fully reverse-engineered from outputs alone.
A new 'Semantic Gambit' adversarial attack exploits language model priors to bypass causal constraints in real-time ASR systems. By augmenting the adversary with predictive LLM context, researchers elevate Word Error Rate to 35.6% — a three-fold increase over state-of-the-art.
PandaAI is a neuro-symbolic LLM agent for quantitative financial analysis. Fine-tuned on financial data and integrated into a closed-loop modular architecture, it combines LLM reasoning with financial rigor. On CSI 300 data: +18.2% Rank IC, −25.7% max drawdown vs SOTA time-series models.
TALAN (Task-Aligned Latent Adaptation Networks) combines a low-rank adapter with a sequence-conditioned latent side path inserted into the transformer's residual stream. Tested on four Qwen3 backbones and four STEM/code benchmarks, TALAN improves LoRA (+1.41 points) and DoRA (+1.85 points) baselines with <1% additional parameters and 1.01-1.02x inference overhead.
Vision paper integrating multi-modal multi-task federated foundation models (M3T FedFMs) into vehicular networks. Combines federated learning with multi-modal foundation models for distributed vehicular intelligence. Validated on Waymo Open Dataset with code released.
Churn prediction framework using 30-day rolling behavioral windows. On real non-contractual data: feature-based model achieves 87.6% accuracy and ROC-AUC 0.94; sequence-based model reaches 96.1% recall. Robustness confirmed on future unseen data (accuracy >83%, ROC-AUC >0.91) without retraining.
Researchers propose PURe (Product-Unit Residual Networks), networks integrating multiplicative units and residual connections to explicitly model nonlinear feature interactions. Evaluation on synthetic benchmarks and real datasets shows improved robustness to noise, efficiency in low-data regimes, and enhanced interpretability via SHAP compared to standard MLPs.
TorchKM is an open-source library for kernel machines (SVM, kernel logistic regression, kernel quantile regression) with GPU acceleration. Scikit-learn-style API, GPU-friendly linear algebra optimization, and intelligent matrix operation reuse. Code available on GitHub, PyPI installation.
RECAP is a benchmark measuring continual prompt adaptation under evolving constraints in production. Six prompt optimization methods evaluated across four LLMs show no significant improvement in proactive protocol (adapt-then-test). Current approaches designed for offline/reactive settings fail in deployment with changing constraints.
Behavioral audit of 7 LLMs (open-weight and closed-source) across 4 US cities reveals racial steering emerges from interaction between user identity, stated preferences, and the model's learned spatial representations. Steering is not uniform: preference-conditioned testing often amplifies bias. Results do not generalize across local markets.
GiFlow, a graph-informed flow matching framework, addresses missing data imputation in spatiotemporal systems (air quality, urban traffic). It replaces standard Gaussian priors with graph-informed priors via spatiotemporal filtering, and uses a hybrid vector field model combining spatial attention, temporal attention, and spatiotemporal propagation. Code available.
ULPS integrates a calibrated LLM into the RL training loop to guide policy via A*-based symbolic trajectories and MC dropout uncertainty. On MiniGridUnlockPickup, the framework improves execution accuracy by 9%, reduces environment interactions, and increases reward AUC over unguided baselines.
Flow matching method to model flux distributions in stochastic particle systems, capturing non-Markovian and non-Gaussian effects missed by classical hydrodynamic equations (regularized Dean-Kawasaki). Validated on Kramers first passage time problem.
Theoretical book proposing a mathematical framework for representation learning in deep networks. Uses optimization and information theory to explain design principles of modern architectures, aiming to demystify mechanisms of large generative models currently treated as black boxes.
New GPLFR method combining Gaussian processes with linear-Gaussian decoding to predict high-dimensional outputs from few training examples. Analytical marginalization of decoder weights couples compression and prediction in a single objective. Application: first spatially resolved emulator of global climate models for rocky exoplanets.
LLMs typically execute all layers in fixed order. This research reveals that dynamic executions (PoLar) can skip or loop layers per input, reducing depth while maintaining or improving accuracy. A lightweight prediction network generates customized execution programs, improving results on mathematical reasoning benchmarks.
WAV v1 improves residual routing in deep Transformers by augmenting block summaries with directional detail bases (phase and split). On TinyStories and Text8, the method reduces validation loss at 48 layers (0.4738 vs 0.4960) with negligible additional parameters.
MacArena is a benchmark of 421 tasks across 50 macOS applications, evaluating computer-use agents on native Apple Silicon environments. Results show leading models drop 26% performance on macOS-native tasks, revealing that existing benchmarks fail to capture genuine cross-platform GUI complexity.
MSFAN neural network classifies 12 polymer types using Terahertz Dual-Comb Spectroscopy. Multi-scale attention architecture with parallel convolutions achieves 85.2% accuracy, outperforming existing models for recycled plastic sorting.
First survey on uncertainty quantification (UQ) in symbolic regression. Examines three approaches: frequentist, Bayesian, and model selection. UQ remains underexplored despite its importance for reliability and real-world decision adoption.
San Diego State University deployed 1,300 AI cameras in student dormitories without notifying residents. The installation raises major privacy and consent concerns.
Academic paper on a new class of worms capable of visually modifying web content in real-time, inspired by digital art techniques. Theoretical security approach exploring client-side rendering vulnerabilities.
Texas grid operator flags risks from growing energy demand by data centers and crypto sites. Multiple facilities failed voltage tests, threatening grid stability.
OpenAI outlines its vision for AI's future, focusing on access, safety, and shared prosperity. The company commits to ensuring AGI benefits everyone.
Developer builds Pocket Node, Android app running llama.cpp on Galaxy Z Fold6. Loads SmolLM3 Q4_0 (1.1B params) via Vulkan backend, SHA-256 model verification, exposes OpenAI-compatible API on Tailscale, integrates homelab monitoring. Limitations: limited context, no RAG, thermal issues under sustained load.
OpenAI launches the Economic Research Exchange to study AI's impact on jobs, productivity, and the economy. Applications are now open for selected research projects.
The open source community is backing OpenEnv, a platform for agentic reinforcement learning. The project gains growing adoption and active collaboration within the open source ecosystem.
Release of datasette-agent-edit 0.1a0, a plugin for Datasette Agent enabling agents to edit text (Markdown, SQL, SVG). Implements three tools inspired by Claude's text editor: view, str_replace, insert.
A r/LocalLLaMA user criticizes Pi, Mario Zechner's agentic framework, for not being optimized for local LLMs. Pi uses a short system prompt and minimal tools, designed for API users (Claude). The author tests Pi on Nemotron and Qwen: local models fail to execute reliable tool calls without enabling reasoning, revealing a fundamental mismatch.
club-3090 adds experimental FP8 quantization support for Qwen3.6-27B. The FP8-quantized model performs virtually identically to the original BF16 version, enabling inference on dual RTX 3090 setups.
User reports llama-server router mode allocates CUDA context on all GPUs even when a model is pinned to one. Gemma 4B on RTX 5060 Ti reserves ~256 MiB per 3090 and ~120 on 4060 Ti, causing OOM when 3090s are saturated. Issue stems from child processes inheriting router env without per-model `CUDA_VISIBLE_DEVICES` support.
Nightwatch is an open-source AI-powered SRE tool operating in read-only mode. Presented on Hacker News with modest engagement (4 points, 2 comments), it offers automation without direct system modifications.
Open-source PyTorch framework for training LLMs with MoE/MoD architectures, custom CUDA kernels (2-7x faster than vanilla PyTorch on T4), up to 64 experts, adaptive training orchestrator monitoring 20+ metrics, configs from 500K to 300B parameters. Apache 2.0, free Colab demo included.
Qwen 3.6 27B scores 1.79% on DeepSWE, ranked 18th above Haiku 4.5. 70-hour benchmark on RTX6000 Blackwell with reasoning enabled and 262k context window. Average 44k output tokens per task, performance on par with similar models despite verbosity reputation.
Article analyzing AI economics through six charts: massive infrastructure investments, growing compute spending, comparison with previous tech bubbles, and questions about actual returns from current deployments.
Hugging Face introduces Room360, a video-to-3D spatial reconstruction platform. The tool converts video sequences into usable 3D models for immersive and architectural applications.
User reports that QAT variant of Gemma-4 26B A4B (google/gemma-4-26B-A4B-it-qat-q4_0-gguf and unsloth/gemma-4-26B-A4B-it-qat-GGUF:Q4_K_XL) produces degraded results on a chessboard SVG test with llama.cpp b9549, compared to the older non-QAT version which performs correctly.
Control 3D avatars with natural language using programasweights, which compiles English descriptions into action programs executed locally in the browser. Supports complex sequences ("walk while waving, then jump twice") without predefined buttons. Partially open-source code, targeting game applications.
GMKtec announces EVO-X3 with OCuLink, Wi-Fi 7, and dual PCIe 4.0. A variant with Ryzen AI MAX+ 495 and 192GB RAM planned for late 2024. First known hardware announcement for this processor.
DeepSeek topped Ramp's trending software vendors in June 2026 as a paid service. US companies are adopting it to cut AI costs, but Ramp's chief economist warns of security risks associated with Chinese models.
User reports running Qwen3.6 35B-A3B locally on ASUS Zenbook Pro 14 (RTX 4060 8GB) achieving 27 TPS at 32k context. Model executes CLI commands, manipulates files, and acts as thinking partner. Author now prefers local models for sensitive data while retaining cloud models for public projects.
A bootstrapped founder examines the ROI of AI coding tools. The calculation differs for unfunded startups: API costs, actual productivity gains, and development velocity impact follow different economics than venture-backed companies.
Open-source utility to launch llama-server with centralized configuration and model management. Supports multiple llama-server binaries, per-model overrides, and command-line overrides. Available on GitHub.
Analysis of inference costs: Anthropic and OpenAI may spend 10x more per user request than revenue generated. Operating margins appear negative at scale, raising questions about the economic viability of current models.
MTP (Multi-Token Prediction) support for Gemma4 merged into llama.cpp. This optimization enables faster token generation by predicting multiple tokens simultaneously.
Pull request to add Gemma4 MTP support in llama.cpp. Performance improvement for local Gemma execution.
Google integrates users as unpaid search quality raters. The system implicitly collects satisfaction signals through user interactions to refine ranking algorithms.
llama.cpp is a C/C++ project for LLM inference. Available on GitHub, it enables efficient execution of language models in C/C++.
TurboVec is a vector index built on TurboQuant, written in Rust with Python bindings. Optimized for high-performance vector search.
Goose is an open-source, extensible AI agent that goes beyond code suggestions—it installs, executes, edits, and tests with any LLM.
Cline is an autonomous coding agent available as SDK, IDE extension, or CLI assistant. Open-source tool for automating development tasks.
Visual, example-driven guide to Claude Code from basic concepts to advanced agents, with copy-paste templates for immediate implementation.
TurboVec is a vector index built on TurboQuant, written in Rust with Python bindings. Optimized for high-performance vector search.
Curated collection of 500 AI agent projects across healthcare, finance, education, retail and more. Practical use cases with links to open-source implementations.
KaliGPT is a multi-model agentic AI (Gemini, ChatGPT, Ollama, OpenRouter) fine-tuned for ethical hackers and offensive security students. Streamlines penetration testing workflows.
AstrBot is an AI agent framework integrating multiple IM platforms, LLMs, and plugins. Open-source alternative to OpenClaw for building AI assistants.
DeskDash is a free Windows tool to easily manage GGUF files. Community-developed, it simplifies organizing and using locally quantized models.
Full KV cache quantization benchmark for Qwen 3.6 27B: 75 pairs tested with q8/q6/q5/q4, KVarN, Turbo/TCQ. Detailed results and analysis published. BeeLlama.cpp (llama.cpp fork) used as inference engine.
Two independent researchers (M.Eng, ex-European research institutes) seeking arXiv cs.CV endorser for Locate-SAM2 paper. Training-free pipeline connecting NVIDIA's LocateAnything-3B to Meta's SAM 2.1 via lightweight adapter. RefCOCO val: 0.772 mIoU vs 0.717 for Grounding DINO Base. Code and paper available.
OpenAI offers Codex vouchers to Hugging Face sponsors to test the code generation model. Partnership initiative between OpenAI and the community platform.
Lathe is a tool that leverages LLMs to deepen learning in a new domain rather than bypass it. Shared on Hacker News, the project offers a pedagogical approach where language models facilitate progressive understanding.
OpenAI plans a major overhaul of ChatGPT, transforming it into a "superapp" bundling coding tools, AI agents, and partner apps (Canva, Booking.com). Internally, the company states "chat is dead" and bets on autonomous agents to handle tasks.
Dockerized Nemotron 3.5 ASR implementation replacing Parakeet. Supports 40+ locales, native streaming architecture, achieves 4.5x realtime speed on CPU with onnxruntime-genai backend. GPU support untested.
Perplexity introduces "Search as Code", an architecture letting AI models write their own search pipelines in Python instead of calling fixed APIs. The system outperforms OpenAI and Anthropic on key benchmarks while reducing token costs by up to 85%.
Hugging Face releases Her, a debugging tool for Claude Code sessions. Her analyzes interactions and identifies issues in AI-assisted coding workflows.
Practical guide to build a distributed cluster with 3 Jetson Nano Orin Super (1024 CUDA cores, 8GB LPDDR5). Educational series on distributed learning using existing hardware (Raspberry Pi, Mac mini, Jetson). Multi-device heterogeneous inference and training demonstrations.
OpenAI launches Lockdown Mode for ChatGPT, disabling web access, Deep Research, and Agent Mode to reduce data exfiltration risks from prompt injection attacks. The mode blocks the final step of the attack but does not fully solve the problem.
New approach for single-image diffusion models that generates images without additional training. The method is computationally efficient and memory-optimized.
Researcher shares collection of 1700 arXiv papers organized into 90 categories since ChatGPT launch. Migrated from Obsidian to web with 6000 'Inquiring Lines' (cross-cutting syntheses) and wiki links between papers. Includes prompts to discover related recent research.
Clive Chan, OpenAI's second hardware engineer, joins Anthropic. He brings experience from Tesla Autopilot ASICs and the OpenAI-Broadcom partnership. Both companies prepare for IPOs while Anthropic considers developing its own AI chips.
A study comparing models from 4M to 4B parameters reveals small models fail at rare tasks because frequent ones constantly overwrite learned skills. A practical solution: increase target task frequency in training data rather than scaling up the model.
Discussion on methodology for comparing Gemma 4 31B original vs QAT-retrained Q4 quantizations. Author proposes benchmarking unquantized versions first (SuperGPQA, HLE, MMLU) then measuring divergence of each Q4 against its own reference, rather than direct cross-variant comparison.
User runs Gemma-4-26B-A4B on old i5-8500 CPU with 32GB RAM, no GPU, achieving ~7 T/s via Koboldcpp. Recent compressed models make GPUs less essential for local inference.
GraphKV, KV cache compression project using graph embedding models. Achieves 7.76x compression on GPT-2 (cosine 0.999949), 3.36x on Qwen2.5-7B 32k tokens (cosine 0.990316). Inspired by TurboQuant, uses int2/int4/NF4 quantization.
open-deepthink adds knowledge distillation mode using Qualitative Neural Networks (QNN). Agents arranged in layers evolve via Mirror Descent and mutation, generating structured JSON datasets with developmental traces, agent reasoning, and evolutionary history for fine-tuning local LLMs.
Mechanistic interpretability experiment on Qwen3.5-35B-A3B: a routed expert (E114, layer 14) correlates with first-person self-examination register during generation. Author documents results before git release, using W/S/Q decomposition of MoE routing.
Study quantifying token distribution in agentic AI systems for software engineering. Analyzes where and how tokens are consumed across autonomous agent workflows.
Gemma4 12B released 3 days ago includes native vision and audio recognition, supports tool use without external dependencies. Q4 quantization: 8 GB RAM. Performance close to 27B-31B models according to users.
User benchmarks Gemma 4 31B QAT Q4 vs standard Q4 quantization on CPU (Xeon Platinum 8358). KLD metric on 5000 wikitext-2 tokens: Q4_K_M outperforms QAT Q4, which loses to standard Q4_0. Counter-intuitive results, reproducible (3 runs, std dev ±0%).
dvlt.cu is a minimal CUDA/C++ inference engine (5MB binary) for NVIDIA's DVLT 3D transformer model. Zero Python/PyTorch dependencies, uses cuBLASLt and cuTLASS, loads 117M parameters in bf16. Output viewable as HTML (point clouds + camera poses).
LLM Benchy is a unified benchmarking tool for comparing LLM endpoint performance. Inspired by 3D printer Benchy tests, it enables standardized testing across any LLM endpoint with metrics like tokens/s and latency across 11 categories (coding, math, reasoning, etc.). Open GitHub repo accepting contributions.
QAT-matched assistant heads for Gemma 4 (12B, 26B-A4B, 31B) released on HuggingFace for speculative decoding. PARALLEL=2 crash fixed in llama.cpp. QAT-matched heads improve acceptance rate by 7–35 percentage points vs non-QAT heads.
Amateur student seeks critical review of a custom neural network architecture (Directional Neural Network) he designed. The architecture outperforms standard MLPs on simple tasks, but the author suspects potential evaluation bias in his comparisons (initialization, optimizer, datasets). Shares a repository with reproducible code.
Universal Memory Protocol proposed to standardize memory storage and access format across AI agents. Aims to enable interoperability and reusability in multi-agent systems.
Admin account takeover vulnerability discovered in PewDiePie's AI tool. The flaw enables unauthorized access with a single action. Video content NSFW.
Computex 2026 explores the emergence of agentic PCs. The industry debates whether personal computers finally integrate autonomous AI agents capable of executing tasks without constant human intervention.
Hugging Face showcases a collaborative experiment across five labs using small models to build a dramatized financial scenario. The project demonstrates how reduced-size models can be orchestrated to generate complex narratives in a specialized domain.
User reports llama.cpp v9413 benchmarks on dual AMD MI50 with Debian Testing. Using Qwen 3.6-35B-GGUF, Vulkan reaches 977 t/s (PP) and 55 t/s (TG) at concurrency 1; ROCm-MTP delivers 92-115 t/s (TG) at concurrency 2. MTP (Multi-Token Prediction) significantly improves generation throughput.
Google released Gemma 4 12B QAT (Quantization-Aware Training) variant. User achieves 120 tok/s on RTX 4070 Super 12GB with llama.cpp using MTP speculative decoding and draft assistant model. Detailed benchmark across 9 tasks with 65.78% aggregate acceptance rate.
Meta confirms thousands of Instagram accounts were compromised through exploitation of its AI chatbot. Attackers abused the chatbot functionality to bypass security protections and gain unauthorized account access.
Optimus, a semi-supervised learning method for graphs, matches GCN performance with 5× fewer labels. On PathMNIST (2000 nodes, 9 classes), with 9 labels Optimus achieves 73.9% vs 60.6% for GCN. Live demo on Hugging Face Spaces.
KVarN KV cache quantization matches precision of one bit higher: 6-bit KVarN equals q8_0, 4-bit matches q5_0. Benchmarks on Qwen 27B 64k context show major VRAM savings. Implementation in BeeLlama v0.3.2 (llama.cpp fork). Prompt processing slower for now.
A user asked GLM AI (Alibaba's agent) to host a playable Minecraft server. The agent generated the server, created a dashboard, and hosted it in Hong Kong. Demonstrates complex task execution capabilities.