Knowledge catalogue
arXiv:2608.07043v1 Announce Type: cross Abstract: Developing nonlinear models that are both expressive and computationally efficient remains a challenge in machine learning and nonlinear system identi
arXiv:2608.07429v1 Announce Type: new Abstract: Long-term memory enables language agents to reuse past facts, preferences, and task experience. Persistence also creates a central falsifiability proble
arXiv:2608.06467v1 Announce Type: new Abstract: Facial expression recognition (FER) in videos is challenging because models must identify subtle, temporally evolving affective states that vary across
Ran the model with quants (Q4) by Unsloth with latest (build from master) llama.cpp server. It takes ~20GB ram running on M5 Pro with 48GB at about 17t/s. Didn't do any reasoning loops/overthinking. O
arXiv:2608.06396v1 Announce Type: cross Abstract: Mixture-of-Experts (MoE) language models route each token through a small subset of experts, making routing patterns useful for identifying task-relev
// The Bitter Lesson of Tool Calling // Tool calling is a design choice, and the defaults are quietly costing accuracy. How so? New research releases a generation-spanning comparison of programmatic t
arXiv:2608.06663v1 Announce Type: new Abstract: Frontier language models solve reasoning problems in a single forward pass that would have been research contributions years ago, yet fail at multi-hour
The next frontier of Recursive Self-Improvement is Physical AI. Japan sparked the robotics revolution. We are expanding our RSI Lab to build world models that allow agentic reasoning systems to recurs
arXiv:2608.06714v1 Announce Type: new Abstract: Recent systems for optimizing prompts, programs, and ML workflows typically rely on explicit outer-loop controllers such as evolutionary search, bandits
arXiv:2606.15485v2 Announce Type: replace-cross Abstract: Agentic AI systems act autonomously, use tools, adapt to context, and operate in complex real-world environments. However, these same characte
arXiv:2608.06630v1 Announce Type: new Abstract: Pruning reduces the inference cost of large language models, but existing criteria primarily preserve large activations or reconstruct layer outputs. We
The successor to Llama is here, and Meta is revitalizing focus on open weights with their new Muse Glimmer - a leading 30B param model designed for always-on local agent use, small enough to run on a
arXiv:2608.06563v1 Announce Type: new Abstract: Machine learning and optimization have advanced together, with practical demands motivating new theory and theoretical breakthroughs enabling new applic
There is an asymmetry in most agentic workflows that does not get talked about much: humans have many ways to talk to agents, and almost no standardized way for agents to talk back to humans. You can
MIT Technology Review’s What’s Next series looks across industries, trends, and technologies to give you a first look at the future. You can read the rest of them here. Way back in the summer of 2017,
This Meta campaign is a case study in strategic reframing, with 4 major examples: 1) REFRAMES THE AI RACE FROM “who builds it the best” TO “who distributes it to the most people”: Instead of fighting
arXiv:2603.27723v2 Announce Type: replace Abstract: Multimodal-attributed graphs (MAGs) are a fundamental data structure for multimodal graph learning (MGL), enabling both graph-centric and modality-c
arXiv:2608.07274v1 Announce Type: cross Abstract: Split Federated Learning (SFL) facilitates privacy-preserving collaborative training with reduced client-side overhead. However, its split architectur
Together Serverless Inference gives developers a high-throughput, managed production path for running Muse Glimmer across agentic and multimodal workloads. Start building: https://www.together.ai/mode
arXiv:2608.07214v1 Announce Type: cross Abstract: Modern AI is no longer a single model but an ecosystem: classical ML predictors, deep and multimodal models, large language models, and agents, each t
arXiv:2608.06503v1 Announce Type: new Abstract: Recurrent context compression controls context growth in long-horizon agents, but its behavioral effects remain poorly understood. In this preliminary e
arXiv:2608.06599v1 Announce Type: new Abstract: Mandibular reconstruction restores facial continuity and oral function after segmental resection. Patient-specific cutting guides transfer a computed to
arXiv:2403.00802v2 Announce Type: replace-cross Abstract: Production-grade recommender systems rely heavily on a large-scale corpus used by online media services, including Netflix, Pinterest, and Ama
arXiv:2608.07317v1 Announce Type: cross Abstract: The AI-Native Manifesto envisions large-scale agile software development in which humans increasingly govern intent, risk, and exceptions while agents
arXiv:2608.06394v1 Announce Type: new Abstract: Multi-label node classification is an important yet challenging task in graph learning, where nodes exhibit multiple semantics simultaneously. Existing
arXiv:2608.06657v1 Announce Type: new Abstract: Modern cyber-physical and AI-assisted systems couple human operators, AI decision modules, and automated controllers in a single control loop, so trustw
arXiv:2608.06549v1 Announce Type: cross Abstract: LLMs are increasingly being applied to tasks involving institutional and political texts, but existing benchmarks evaluate them on isolated documents
arXiv:2608.07371v1 Announce Type: cross Abstract: Recent agentic reinforcement learning methods use hindsight to complement sparse outcome rewards. However, a completed rollout can yield many such sig
Obviously nobody needs a transformer that's good at multiplication. I wanted to know whether a stock transformer could do exact arithmetic if I chose its weights directly. I implemented the grade-scho
arXiv:2608.07077v1 Announce Type: new Abstract: The Tower of Hanoi is a simple planning puzzle that in prior work has proven challenging for large reasoning models (LRMs). Current models solve the sta
arXiv:2608.06407v1 Announce Type: cross Abstract: Automated Sign Language Recognition for under-represented languages remains a largely unsolved problem. Central African Sign Language (CASL) exemplifi
arXiv:2608.06926v1 Announce Type: new Abstract: Designing autonomous agents that effectively assist human teams hinges on understanding team dynamics, often without task specific knowledge. We present
arXiv:2608.06404v1 Announce Type: new Abstract: Accurate 3D crop monitoring underpins data-driven precision agriculture by enabling field-scale analysis of plant structure, growth dynamics, and manage
The TileRT InferenceX article (Aug 10 2026) examines whether the TileRT software stack on NVIDIA GPUs can compete with dedicated inference systems such as Cerebras, Groq LPUs and SambaNova for ultra‑h
Ultra-High Interactivity on NVIDIA GPUs? TileRT InferenceX Can TileRT software on NVIDIA GPU compete with Cerebras, Groq LPU, SambaNova? Batch Size 1, Disaggregated engine, High throughput prefill eng
arXiv:2608.07398v1 Announce Type: cross Abstract: Production planning in the manufacturing industry often relies on the use of optimization models, but defining an appropriate objective function can b
arXiv:2608.07015v1 Announce Type: new Abstract: Omni-domain infrared small target (IRST) detection is crucial for infrared surveillance, yet remains challenging due to heterogeneous imaging domains an
arXiv:2608.06809v1 Announce Type: new Abstract: How can an analyst decide whether a nonlinear dimensionality reduction embedding can be trusted? Existing diagnostics provide only partial answers: proj
arXiv:2608.06784v1 Announce Type: new Abstract: Bidirectional unpaired image translation must preserve source-specific structure while learning coherent transformations in both directions without pair
arXiv:2608.07409v1 Announce Type: new Abstract: Joint-Embedding Predictive Architectures (JEPAs) have emerged as a principled framework for self-supervised learning of world models in compact latent s
arXiv:2511.01295v3 Announce Type: replace Abstract: Recent advances in multi-modal generative models have driven substantial improvements in image editing. However, current generative models still str
arXiv:2608.06511v1 Announce Type: new Abstract: Adaptive data-cleaning methods replace manual filtering thresholds with data-driven partitions. However, changing the partition granularity, the number
arXiv:2608.06833v1 Announce Type: new Abstract: Image-goal navigation is a fundamental capability for embodied AI, yet its practical deployment is strained by strong prior assumptions. Existing method
arXiv:2608.07053v1 Announce Type: new Abstract: Pretrained partial differential equation (PDE) foundation models can generalize across different equations, but adapting them to unseen PDE systems typi
Enterprise Java developers have a new superpower—drive GitHub Copilot from idiomatic Java code with annotations, virtual threads, and more. The post Using the GitHub Copilot SDK for Java appeared firs
Muse Glimmer Note: Muse Glimmer is currently available via initial support via Ollama's MLX engine on Apple Silicon. Additional support and optimizations for Apple Silicon, NVIDIA, AMD, and other plat
v0.32.8 is an Oct 10, 2023 release of the ollama repository on GitHub, following a pre‑release tag v0.32.8‑rc0. The update adds Muse Glimmer support for NVIDIA, AMD and additional platforms, with the
arXiv:2608.06668v1 Announce Type: new Abstract: As an important component of the supply chain industry, transportation has experienced rapid development in the past decade with the assistance of digit
arXiv:2608.06919v1 Announce Type: new Abstract: LiDAR serves as a primary sensing modality for robots operating in outdoor environments. However, the performance of deep learning models in this domain
Very cool idea to have agents design complex systems by searching over the model structure itself. New research from Sakana AI introduces CEDAR, which uses LLM agents to write, simulate, and refine sy
Voyage AI models now run natively on Fireworks, the first and only dedicated inference platform @VoyageAI by @MongoDB has partnered with. Embed, retrieve, rerank, generate: your full retrieval pipelin
arXiv:2608.06934v1 Announce Type: cross Abstract: Visual perception of walkability varies substantially across individuals, reflecting differences in personal characteristics, experiences, and prefere
arXiv:2608.07433v1 Announce Type: cross Abstract: Wasserstein policy gradient (WPG) updates state-conditional action laws by transport in the action space. We study entropy-regularized discounted line
arXiv:2608.06717v1 Announce Type: new Abstract: Diffusion-based face restoration that adjusts the sampling trajectory of pre-trained diffusion models has achieved remarkable progress. However, existin
We asked an unreleased research version of Claude to take a stab at the Riemann hypothesis. It didn’t solve it, but it did make strides on a related problem: it increased the lower bound for the fract
arXiv:2608.06823v1 Announce Type: cross Abstract: In this paper, we extend a weak adversary neural network pushforward method for solving time dependent Boltzmann equation and a weak formulation of th
arXiv:2608.06474v1 Announce Type: new Abstract: Large language models increasingly generate complete websites from natural-language descriptions, and reinforcement learning has become a central approa
arXiv:2608.06704v1 Announce Type: new Abstract: Delegating a web task involves more than asking a question; it requires transferring a policy: what to verify, how to handle uncertainty, which preferen
We’re expanding our cybersecurity initiative Daybreak and introducing GPT-5.6-Cyber, a new model for advanced, authorized cybersecurity work. As the threat landscape evolves, we’re putting frontier in
OpenAI announced the release of GPT‑5.6‑Cyber as part of its Cybersecurity Initiative, “Daybreak.” The model is aimed at advanced, authorized security research and testing, helping trusted defenders d