Search: “research”

arXiv:2608.30277v1 Announce Type: new Abstract: The unprecedented surge in Earth observation data volume and diversity has exposed a critical bottleneck for traditional manual workflows, catalyzing th

arXiv:2605.05726v2 Announce Type: replace Abstract: As LLM agents are increasingly deployed with large libraries of reusable skills, selecting the right skill for a user request has become a critical

arXiv:2509.18123v2 Announce Type: replace Abstract: Accurate interpretation of soil moisture patterns is critical for irrigation scheduling and crop management, yet existing approaches for soil moistu

arXiv:2402.03741v4 Announce Type: replace-cross Abstract: Recent advancements in multi-agent reinforcement learning (MARL) have opened up vast application prospects, such as swarm control of drones, c

arXiv:2608.29023v1 Announce Type: new Abstract: Human-robot collaboration describes the process of humans and autonomous agents working together to accomplish common goals. This process is facilitated

arXiv:2608.28597v1 Announce Type: new Abstract: Online surveys are a foundational data collection instrument in a variety of fields, with attention checks serving as critical guardians of response qua

The ultimate Grok @bot set up for me is to filter EVERYTHING - absolutely everything through one agent and hide everything else. That agent is in charge of as many agents as needed that will own speci

arXiv:2603.04191v2 Announce Type: replace Abstract: Large Language Models (LLMs) are increasingly serving as personal assistants, where users may share individual preferences over extended interaction

arXiv:2608.31117v1 Announce Type: cross Abstract: Generative models have become central across science and industry, from image and text synthesis to the design of molecules and materials. Quantum gen

arXiv:2604.18364v2 Announce Type: replace Abstract: Generating programmatic animation using libraries such as Manim presents unique challenges for Large Language Models (LLMs), requiring spatial reaso

arXiv:2608.30391v1 Announce Type: cross Abstract: Understanding agent behavior requires methods that scale to thousands of trajectories and surface new patterns in long, often unfamiliar tasks where p

arXiv:2608.27505v1 Announce Type: new Abstract: Reinforcement learning from human feedback (RLHF) has become the dominant paradigm for aligning large language models (LLMs) with human preferences. How

“AI won't kill us, but the superposition of greed and stupidity certainly will.” This is becoming more and more of something I 'smelled' from the beginning, a real shit show. I initially said that Ope

All week we’re spotlighting teams training past the frontier on Fireworks. @Figma’s AI team is shipping features that change how millions of people design, and with the Training API they can iterate f

arXiv:2608.28394v1 Announce Type: cross Abstract: Cyber threat intelligence (CTI) is foundational to modern cyber defense, yet much of it resides in unstructured reports whose volume and heterogeneity

arXiv:2608.28070v1 Announce Type: new Abstract: Automated detection of surface micro-defects on industrial components, such as copper tubes, is critically important for quality assurance but remains c

arXiv:2505.15450v3 Announce Type: replace Abstract: Text-to-image diffusion models have gained widespread application across various domains, demonstrating remarkable creative potential. However, the

// ContextLeak in AI Agents // The whole attack surface here is a tool name and a tool description. Stealing an LLM agent's runtime context, meaning the user prompt, the execution trajectory and the t

arXiv:2305.12474v4 Announce Type: replace Abstract: Large Language Models(LLMs) have demonstrated remarkable performance across various natural language processing tasks; however, how to comprehensive

arXiv:2608.27844v1 Announce Type: new Abstract: Existing evaluations of harmful content detection rely predominantly on static benchmarks, which struggle to reflect the interactive adversarial ecosyst

I keep seeing demos of AI agents building scenes in Blender through BlenderMCP, so I tried it myself. I ran both models locally for this and picked the GLM 5.3 family(Q4 quant) because videos of it do

I am the product lead for the training platform at @FireworksAI_HQ . Today the Training API and Fireworks Lab are GA. I won’t walk you through all the features. I want to tell you why teams train with

My conversation with @jerryjliu0. He's building @llama_index: document infrastructure for AI agents, the layer underneath everything models need to work. Did you know he's the guy whose tool half the

[new @activegraphai blog post] How Synthetic Players used ActiveGraph to verify 4,919 runs without new model calls https://activegraph.ai/blog/synthetic-players-activegraph-replay For the increasing n

arXiv:2603.28387v3 Announce Type: replace-cross Abstract: Trustworthy clinical AI must use real evidence and avoid relying on surface-level artifacts. We evaluate 12 open-weight vision-language models

arXiv:2504.04342v2 Announce Type: replace Abstract: Scaling up model parameters and training data consistently improves the performance of large language models (LLMs), but at the cost of rapidly grow

## Qwen3.8-Flash-Next-NVFP4 (inferact) vs Qwen3.8-27B-FP8 (qwen) Slammed with work and no time to pretty this up. Qwen wrote most of this but I checked the data. All tests done on the same rig, same p

TL;DR: Ninfer/DS4 but for RDNA4 Highly custom kernels built for RDNA4, applied to vLLM-Radiance to greatly improve Qwen3.8 Flash Next speeds. This is mostly for dual R9700s with preferably 48GB of RAM

arXiv:2511.14684v2 Announce Type: replace Abstract: Large language models (LLMs) often make reasoning errors when solving mathematical problems, and how to automatically detect and correct these error

arXiv:2608.27843v1 Announce Type: new Abstract: Contemporary language models can converse fluently and influence human decisions, yet their exchanges do not enter a continuing, vulnerable life of thei

arXiv:2608.27948v1 Announce Type: new Abstract: Test-time adaptation (TTA) on graphs aims to adapt a graph neural network (GNN) that is well-trained on the training graph to the test graph, which invo

arXiv:2608.28152v1 Announce Type: cross Abstract: Agitation fluctuates over short time horizons in people living with dementia, yet continuous physiological information for anticipating next-day risk

Hey guys I have been working on a open source LLM development repo. Anyone can train any amount of parameter against any arch (GQA, MLA, Dense...) When I tried to implement MLA I read the technical re

Artificial intelligence agents are moving from experimentation to production, and with this shift, the stakes are rising. A coding agent at PocketOS recently deleted an entire production database. An

at the end of the day, we all have to stand by our company and the values it represents 🙂 * frontier labs will want to own their own application/harness/model e2e. or at least, openai will to start wi

You do not need frontier models for everything. For example, open models are great for automations. If you are not sure where to adopt open models, start there. It's one of the biggest changes I've ma

arXiv:2608.26177v1 Announce Type: cross Abstract: Long-form generation exposes fundamental limitations of large language models. Even 70B-parameter models exhibit length collapse at 16k-token outputs,

arXiv:2608.26130v1 Announce Type: new Abstract: Coding agents built on large language models (LLMs), such as Claude Code, Cursor, OpenAI Codex, GitHub Copilot, and Aider, receive tool responses that r

Anthropic PBC today previewed a standard that makes it easier for artificial intelligence agents to control machines such as microscopes. The Model Hardware Standard, or MHS, is the fruit of a collabo

arXiv:2608.26921v1 Announce Type: cross Abstract: We introduce AraMS-28k, the largest publicly released line-level dataset of genuine historical Arabic manuscripts, comprising 14 books, 3,043 pages, a

arXiv:2608.26807v1 Announce Type: cross Abstract: Travel planning agents assist users in generating personalized travel plans by modeling their individual preferences. Existing agents either rely on e

arXiv:2601.17173v2 Announce Type: replace-cross Abstract: Question answering systems are typically evaluated on factual correctness, yet many real-world applications-such as education and career guida

arXiv:2608.27268v1 Announce Type: new Abstract: Although Large language models (LLMs) mediate access to knowledge and computational assistance, their capabilities should benefit vulnerable groups in t

arXiv:2608.26114v1 Announce Type: new Abstract: Calculation-intensive financial question answering requires exact reasoning over structured rates, temporal conditions, numerical formulas, and rule-bas

arXiv:2608.26173v1 Announce Type: cross Abstract: Students and working professionals have to go through the attendance process every day. Traditional methods of marking attendance using pen and paper

arXiv:2608.27244v1 Announce Type: cross Abstract: An LLM call in a semantic data processing system is expensive enough to dominate query cost, yet slow enough to hide a CPU-side learner's update behin