Knowledge catalogue
arXiv:2607.05583v1 Announce Type: cross Abstract: Contemporary language models are dominated by the transformer architecture, which leverages self-attention mechanisms to enable more efficient, parall
arXiv:2607.04689v1 Announce Type: cross Abstract: Safe operation of autonomous vehicles in dense urban traffic depends on perception and planning that remain reliable when onboard sensing is degraded.
arXiv:2512.18176v2 Announce Type: replace Abstract: Accurate segmentation of anatomical structures in medical images is essential for diagnosis and treatment planning. While recent interactive segment
arXiv:2607.03453v1 Announce Type: cross Abstract: Inference-time alignment methods, such as Best-of-N, offer a flexible alternative to training-based alignment by using reward models to select high-qu
Swyx appeared in an interview on Local AI that was subsequently featured in The Daily Context newsletter from AIEngineer, with the interview appearing on the second page of that publication. The inter
arXiv:2607.04816v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models have become a promising paradigm for generalist robot manipulation, where visual-language representations are used t
arXiv:2512.08029v3 Announce Type: replace-cross Abstract: Clinical decision-making in oncology requires predicting dynamic disease evolution, a task current static AI predictors cannot perform. While
In this post, we walk through what Dataset Enrichment is, how it differs from legacy Topics, and provide three migration scenarios with step-by-step guidance so you can move your business context into
We found a way to run GLM-5.2 with full context in vLLM without pruning. - top 32 experts NVFP4 - rest fp3 - intel autoround calibration - MXP8 attention - bf16 routers and embedded sees On 3 DGX spar
true. a lot of people here just don’t have the historical context. You know what's funny but not funny: If the housing market of 2006 was the AI market of 2026, Charles R Morris would be getting calle
arXiv:2607.02283v1 Announce Type: cross Abstract: In-context learning (ICL) operates via implicit gradient descent embedded in the forward pass of modern AI architectures -- Transformers, Mamba, state
arXiv:2607.01831v1 Announce Type: cross Abstract: Long-context inference is increasingly common in large language model (LLM) serving, driven by retrieval-augmented generation and agentic systems. In
arXiv:2607.00766v1 Announce Type: new Abstract: Text-to-image personalization aims to generate a user-provided subject in novel scenes described by text. However, most existing methods encode subject
Our CEO @vipulved on @CNBC with @dee_bosa: your data is your recipe. As models get smarter, sending proprietary workflows, customer context, and business logic into closed systems becomes a strategic
arXiv:2510.14819v3 Announce Type: replace Abstract: Trajectory representation learning (TRL) aims to encode raw trajectory data into low-dimensional embeddings for downstream tasks such as travel time
arXiv:2606.32012v1 Announce Type: cross Abstract: Uncertainty estimation has been a long-standing challenge in AI models; it amounts to 'knowing what you don't know,' and metacognition is notoriously
arXiv:2606.31519v1 Announce Type: cross Abstract: Long-context Large Language Model inference is severely bottlenecked by the massive Key-Value (KV) cache, yet existing sparse attention methods often
This is exactly why we believe in customization. Quick context: Factory's original secret scanner was deterministic, so it either flagged things that weren't actually secrets (false positives) or miss
we built the @hyperspell filesystem around this principle every source in your company feeds into a context graph where we resolve conflicts and assign permissions there’s a filesystem on top of the g
Wow and soon after that @mitsuhiko came by and also expressed interest in analysis of token usage in reviews, a perfect use case for context-lens! I didn’t wake up thinking I’d show my work to @simonw
arXiv:2606.28926v1 Announce Type: cross Abstract: In-context learning (ICL) is an emerging paradigm that employs the semantic information inherent in large language models (LLMs) for generating answer
arXiv:2606.28601v1 Announce Type: cross Abstract: Recent progress in Text-to-SQL has been driven by stronger language models and prompting strategies, yet performance on real enterprise benchmarks suc
arXiv:2606.28592v1 Announce Type: new Abstract: Physical caregiving robots need to assist different users with different tasks in diverse environments, and they come in many embodiments. While substan
arXiv:2602.13562v2 Announce Type: replace-cross Abstract: While reasoning models have achieved remarkable success in complex reasoning tasks, their increasing power necessitates stringent safety measu
we launched code interpreters for deep agents last month. Basic idea is to let agents plan, delegate, and organize context using code instead of chained tool calls Code interpreters don't need a sandb
ok for context this is non-lab workshops at 9am on a monday theres a competing @OpenAI workshop going on next door but here are the @snyksec , @Atlassian, @neo4j, @arizeai, @Akamai, @togethercompute r
arXiv:2509.19671v3 Announce Type: replace Abstract: Public datasets of Chest X-Rays (CXRs) have long been a popular benchmark for developing machine learning (ML) computer vision models in healthcare.
🧑🏫3hr Long Deep Agents Course Great course from a member of the community on Deep Agents Covers task planning, file systems for context management, subagent-spawning, and long-term memory https://www
arXiv:2606.26519v1 Announce Type: new Abstract: Large language models (LLMs) can make scientific software easier to use. However, a general model does not automatically know which measurements a parti
arXiv:2606.27233v1 Announce Type: cross Abstract: We present a conceptual framework for analyzing dialogue in collaborative problem-solving contexts, with an emphasis on the emerging dynamics of human
arXiv:2606.27306v1 Announce Type: new Abstract: Translation cascades for reasoning translate the query from another language to English, reason in English, and translate the answer back to the origina
arXiv:2606.26493v1 Announce Type: new Abstract: Diffusion language models offer a promising alternative to autoregressive models due to their potential for parallel and iterative generation. However,
arXiv:2606.26666v1 Announce Type: new Abstract: Autoregressive large language model (LLM) serving is increasingly limited by key-value (KV) cache movement rather than dense matrix multiplication. Mode
arXiv:2510.01163v2 Announce Type: replace Abstract: The factors driving the performance of in-context learning (ICL) in large language models (LLMs) remain poorly understood despite ICL's surprising e
arXiv:2606.25907v1 Announce Type: new Abstract: Diffusion models have shown promise in drag-style editing. Previous works mainly focus on point-based drag, which is inherently ambiguous. This paper fo
People are not getting how significant this news – The White House delaying GPT 5.6 – is. Here’s the context and a suggestion. Both @pmarca and @DavidSacks did everything in their power to keep the Wh
What happens when you shift more of the context layer into the model weights themselves? Engram is building a neolab focused on memory and continual learning. Let’s go @dan_biderman @realJessyLin! Fun
We open-source Qwen-AgentWorld-35B-A3B (MoE, 35B/3B active, 256K context) and AgentWorldBench. Two routes, one roadmap: 🔬 Build the simulator — scalable, controllable, surpassing real environments 🧠 I
David Gewirtz / ZDNET: Anthropic launches Claude Tag, an agentic AI coworker for Slack that can learn context, give suggestions, and more, in beta for Claude Team and Enterprise tiers — ZDNET's key ta
Single-shot generation still surfaces net-new kernels with no public reference: NeMo vocab-parallel log-probs, Hyena context parallelism, SAM 3 mask suppression. One GEMM + All-Gather kernel hit 87.9µ
With agentic coding, complexity compounds in a mechanical way: unnecessary code ends up in the codebase, moves to the context window, degrades the model's reasoning abilities, leads to more unnecessar
context engineering docs for agentic engineering - plans, research, etc SHOULD NOT be stored in version control: A good docs management system keeps them: > outside your repo > accesible to agent via
arXiv:2606.11961v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used as conditional generators for structured data, relying on in-context learning (ICL) to adapt to new
arXiv:2606.12411v1 Announce Type: new Abstract: Modern conversational agents condition on an ever-growing dialogue history at each turn, incurring redundant attention and encoding costs that grow with
arXiv:2606.12028v1 Announce Type: new Abstract: Generalizable robot manipulation requires not only task-level reasoning over unseen scenes, but also reliable grounding of visual plans into embodiment-
arXiv:2606.10662v1 Announce Type: cross Abstract: Multi-agent systems (MAS) can scale large language model reasoning at test time by decomposing complex problems into parallel subtasks. However, most
Ram Iyer / TechCrunch: New York-based Jedify, whose platform connects to enterprises' knowledge sources via APIs to build a “context graph” for AI agents, raised a $24M Series A — AI vendors promote t
paper #1 for context: https://x.com/yoheinakajima/status/2057812713045377055?s=20 babyagi has ~200 citations, but 0 papers... i just published my first paper on arXiv 😆 'The Log is the Agent: Event-So
arXiv:2606.10537v1 Announce Type: new Abstract: Diffusion large language models (dLLMs) re-encode the entire prefix at every denoising step, causing recomputation that scales quadratically with contex
arXiv:2606.08151v1 Announce Type: new Abstract: Tool-using LLM agents often fail not because relevant text is absent, but because decisive evidence is not selected, compressed, or surfaced at action t
arXiv:2606.07560v1 Announce Type: cross Abstract: Function-vector (FV) heads (Todd et al., 2024) are typically identified by the magnitude of their causal contribution to in-context rule tasks, under
arXiv:2606.09105v1 Announce Type: new Abstract: Generating novel, feasible, and high-quality research ideas is an important yet challenging task in scientific discovery.Recent Large Language Model (LL
arXiv:2606.07703v1 Announce Type: cross Abstract: Long-context prefill remains expensive because full/GQA layers still score the historical sequence, even in hybrid models with local, sparse, linear,
arXiv:2509.24762v3 Announce Type: replace Abstract: Modeling event sequences of multiple event types with marked temporal point processes (MTPPs) provides a principled way to uncover governing dynamic
arXiv:2606.09271v1 Announce Type: cross Abstract: Parkinson's disease (PD) is a progressive neurodegenerative disorder that frequently causes speech impairments associated with hypokinetic dysarthria.
arXiv:2506.06891v3 Announce Type: replace Abstract: We study the corruption-robustness of in-context reinforcement learning (ICRL), focusing on the Decision-Pretrained Transformer (DPT, Lee et al., 20
Zac Hall / 9to5Mac: Apple announces Siri AI, with on-screen awareness, personal context understanding, a Dynamic Island-based interface, and more, along with a new Siri app — At WWDC 2026, Apple is de
arXiv:2606.06814v1 Announce Type: cross Abstract: The transformer's emergent ability to perform in-context learning (ICL) has sparked a wide range of studies designed to understand its underlying mech
The Top AI Papers of the Week (May 31 - June 7) - LEAP - AutoLab - Learn From Your Own Latents - Reusable Context Engineering - Self-Revising Discovery Systems - Scaling Laws for Agent Harnesses - Dis
arXiv:2606.05339v1 Announce Type: cross Abstract: MCP (Model Context Protocol) enables LLMs (Large Language Models) to interact with external tools and data sources via a standardized protocol. Its ra