Knowledge catalogue
arXiv:2601.20209v2 Announce Type: replace Abstract: Reinforcement learning has empowered large language models to act as intelligent agents, yet training them for long-horizon tasks remains challengin
arXiv:2606.22639v1 Announce Type: cross Abstract: Contextual bandit algorithms have transformed modern experimentation by enabling real-time adaptation for personalized treatment. Yet these advantages
arXiv:2511.14445v2 Announce Type: replace-cross Abstract: We present Tell Me, a mental well-being system that leverages advances in large language models to provide accessible, context-aware support f
arXiv:2606.23123v1 Announce Type: new Abstract: Deep learning models, particularly Transformers and Neural Operators, exhibit a well-documented 'spectral bias,' effectively acting as low-pass filters
This post likely argues that modern AI systems are shifting focus from modeling human cognition and reasoning to instead learning from and operating within the complexities of the real world and physi
arXiv:2606.22959v1 Announce Type: cross Abstract: Latent diffusion approaches to sign language production (SLP) rely on an initial stage that learns an encoding of sign pose sequences, enabling genera
arXiv:2606.21514v1 Announce Type: new Abstract: Recently, Muon has gained substantial attention as an appealing alternative to Adam-like optimizers, with many works highlighting its advantages through
arXiv:2606.23286v1 Announce Type: new Abstract: Sorting a huge stream of waste accurately within a short period can be done with the support of digitalization, particularly Artificial Intelligence, in
arXiv:2508.05762v3 Announce Type: replace-cross Abstract: Universal machine learning force fields (UMLFFs) promise to revolutionize materials science by enabling rapid atomistic simulations across the
arXiv:2606.23204v1 Announce Type: new Abstract: Large-scale image-text datasets, such as LAION-5B, are foundational to modern AI systems, yet their vast scale and uncurated nature raise significant co
arXiv:2606.20711v1 Announce Type: new Abstract: UI videos provide a natural input for generating interactive webpages, as they capture both webpage appearance and action-triggered state transitions. H
arXiv:2606.22870v1 Announce Type: new Abstract: Recent advancements in chain-of-thought (CoT) reasoning have shown promise in enhancing video understanding and reasoning capabilities of multimodal lar
arXiv:2606.20728v1 Announce Type: new Abstract: Vision foundation tools such as open-vocabulary detectors, segmentation models, and post-processing operators are powerful building blocks for computer
arXiv:2606.16196v2 Announce Type: replace-cross Abstract: Deep neural networks have achieved remarkable performance across medical imaging tasks, yet their tendency to overgeneralize under distributio
you need docs built for agents Docs are the eyes and ears of Agents. But we're moving so fast that they are always outdated. So hence an outdated doc also confuses the models. But it's also hard keep
In this post, you will learn how Ampersend built a pay-per-intelligence routing layer on top of Amazon Bedrock AgentCore Payments. AI agents autonomously route tasks to the most effective model, pay p
This guide from OpenAI covers techniques for optimizing the use of Codex (their code generation model) for extended programming tasks and projects that require sustained AI assistance. It likely discu
Deep Agents v0.6 feature spotlight: a code interpreter. Agents can now call tools from inside a runtime, keep intermediate results out of model context, and only pass the relevant output back. Fewer r
The US government ordered Anthropic to cut off foreign access to its Mythos 5 and Claude Fable 5 AI models in June 2026, citing national security concerns related to jailbreak vulnerabilities that cou
This post appears to announce or celebrate the discovery or successful implementation of Ollama, a tool for running large language models locally. Based on the enthusiastic tone and source, it likely
A viral Reddit post claimed Krea 2 would be released as open source, but Krea has not confirmed this announcement. Krea 2 is the company's first foundation image model launched in May, designed for ae
Automated lint: 48 errors, 13 warnings, 3 info
LLMs can’t be trusted to follow rules. Which means they can’t be trusted, period. If we are going to solve alignment we must move on. Large language models can be persuaded to break their own rules. N
New piece in @TheAtlantic! We always hear that AI will cure cancer, and I would immediately benefit if it did. But I argue that racing ahead on generalist AI models creates unclear benefits for cancer
Satya Nadella says the public wouldn't tolerate a few AI labs 'doing all of the learning for the world', as Microsoft moves to provide low-cost models and tools (Wall Street Journal) (Visit Techmeme d
LTX-2.3 is a DiT-based audio-video foundation model capable of generating synchronized video and audio, combining key components of modern video generation with open weights designed for local machine
Use Case 2: Financial Time Series Prediction Can an AI agent navigate sequential, no-look-ahead market decisions? Just for fun, we tested Fugu Ultra on 50 weeks of historical data for an anonymized eq
We've kept hearing how GLM-5.2 beats Opus 4.8, and are skeptical of benchmarks - so we tested them on a real bug from the Cline repo. While both models fixed the issue, GLM was the winner in terms of
Release b9753 fixes server progress reporting for loading speculative decoding models and adds a 'stages' list feature . This update includes improvements and optimizations for the llama.cpp server co
The LTX Director 2 + SEED HUNTER workflow is a technique for AI video generation that addresses the LTX model's poor prompt adherence by testing multiple seeds quickly to find promising results, then
The Top AI Papers of the Week (June 14 - June 21): - PreAct - SpatialClaw - Back on Track - OpenClaw-Skill - From Trainee to Trainer - Compositional Skill Routing - Can LLM Agents Infer World Models?
This handbook covers the technical aspects of running large language models efficiently at scale, focusing on GPU optimization techniques including GPU internals, key-value (KV) cache management, batc
Gary Marcus argues that language models are not genuinely intelligent despite their sophisticated outputs, and that they operate fundamentally differently from human cognition. This critique likely ch
Atlantic reporter Alex Reisner recently uncovered four datasets of music being used to train AI models and made them fully searchable for the public. Two of the sets are absolutely enormous at 12 mill
TSAuditor is a contamination auditing framework for time series foundation models that uses probe adaptation dynamics to detect when evaluation datasets may have been exposed during pretraining, valid
arXiv:2606.12186v1 Announce Type: new Abstract: Enthymemes, arguments with unstated premises or conclusions, are pervasive in persuasive discourse, yet their annotation remains notoriously subjective.
arXiv:2606.12126v1 Announce Type: new Abstract: Existing computational pathology methods predominantly operate within whole-slide image (WSI)-level multiple instance learning (MIL) paradigms, while pa
Anthropic PBC Chief Executive Dario Amodei is calling on the U.S. government to block the deployment of dangerous artificial intelligence models in the same way as it prevents unsafe airplanes from ta
arXiv:2606.12384v1 Announce Type: cross Abstract: Recent advances in agentic Reinforcement Learning (RL) have substantially improved the multi-turn tool-use capabilities of large language model agents
arXiv:2604.06961v2 Announce Type: replace Abstract: Fairness in human-robot interaction critically depends on the reliability of the perceptual models that enable robots to interpret human behavior. W
arXiv:2305.06145v2 Announce Type: replace Abstract: In cloth-changing person re-identification (CCReID), it is critical to learn clothes-invariant feature, which can provide discriminative ID features
arXiv:2606.11953v1 Announce Type: new Abstract: Hateful videos have become prevalent on online platforms, highlighting an urgent need for effective detection. However, existing studies primarily focus
arXiv:2606.11408v1 Announce Type: new Abstract: Action chunking has become a standard design in modern robot policies, from diffusion/flow policies to vision-language-action models, where the policy p
arXiv:2603.08501v3 Announce Type: replace Abstract: Large language models (LLMs) can answer religious knowledge queries fluently, yet they often hallucinate and misattribute sources, which is especial
arXiv:2606.11272v1 Announce Type: cross Abstract: Federated Learning (FL) enables collaborative and privacy-preserving model training across distributed clients, but most existing FL systems implicitl
arXiv:2606.12278v1 Announce Type: new Abstract: Neural network pruning reduces model size by removing less important parameters while aiming to preserve predictive performance. Although the Lottery Ti
arXiv:2606.11290v1 Announce Type: cross Abstract: Large Language Model (LLM)-based multi-agent systems are increasingly powerful, but current agentic workflow optimization paradigms make an unsatisfyi
arXiv:2606.11286v1 Announce Type: cross Abstract: High-content imaging assays quantify cellular responses to chemical and genetic perturbations, yet continuous trajectories of individual cells are uno
arXiv:2606.11572v1 Announce Type: new Abstract: Transfer learning from large-scale RGB foundation models to infrared (IR) imagery through knowledge distillation (KD) remains challenging due to fundame
arXiv:2606.11429v1 Announce Type: cross Abstract: Speech foundation models often struggle in low-resource domains due to domain mismatch and data scarcity. We propose Gumbel-BEARD, a domain adaptation
arXiv:2606.12318v1 Announce Type: cross Abstract: Neural operators approximate mappings between function spaces, but often generalize poorly to other operators and usually require fine-tuning or retra
arXiv:2606.11425v1 Announce Type: cross Abstract: Jailbreak attacks expose persistent safety weaknesses in large language models (LLMs), but existing stateless single-turn methods face a trade-off: ha
arXiv:2606.11585v1 Announce Type: cross Abstract: We introduce Kuramoto attention, a self-attention layer in which each hidden coordinate is an angle. The layer scores tokens by gated cosine similarit
arXiv:2602.05746v2 Announce Type: replace-cross Abstract: Prompt injection is a critical vulnerability in LLM agents, yet the strongest methods still rely on human red-teamers and hand-crafted prompts
arXiv:2606.11560v1 Announce Type: cross Abstract: Large Language Models (LLMs) have advanced rapidly, but their limitations in structured and multi-hop reasoning underscore the need for graph-native,
'Mastery is not about creating more outputs or products. It is about building genuine ability. AI can either decay or support human mastery. The people selling you AI models & your bosses at work don’
arXiv:2606.12279v1 Announce Type: cross Abstract: Recent work in ML applies genetic algorithms at inference time to iteratively improve solutions to optimization problems. The basic mutation and recom
arXiv:2606.12332v1 Announce Type: new Abstract: Evaluating multi-turn dialogue is challenging because quality emerges across turns rather than within individual responses. We focus on a key dimension
arXiv:2606.12146v1 Announce Type: cross Abstract: Rotary Position Embedding (RoPE) is widely adopted in Transformer models, yet its extension to high-dimensional domains lacks a unified theoretical fo
arXiv:2606.11946v1 Announce Type: cross Abstract: The conventional approach to deep learning over relational databases applies neural models, such as Graph Neural Networks (GNNs), to a graph represent