Knowledge catalogue
TTT-Discover is a method that enables models to learn and discover patterns during test time rather than only during training, allowing for adaptation to new data distributions at inference. The appro
Aurora is a unified training-serving system that integrates reinforcement learning with adaptive speculative training to optimize large language model inference and training efficiency. The system dyn
Untied Ulysses is a memory-efficient technique for context parallelism that processes attention heads in chunks rather than sequences, reducing memory overhead during transformer inference and trainin
Opportunistic Expert Activation (OEA) is a batch-aware expert routing technique for mixture-of-experts models that enables faster decoding without requiring model retraining. The method optimizes whic
ParallelKernelBench is a benchmarking framework designed to evaluate large language models' ability to generate optimized GPU kernels for multi-GPU computing environments. The benchmark assesses LLMs
Krea 2 is a technical advancement in AI image generation with newly released model weights available for download on GitHub. The technical report details the improvements and capabilities of this vers
arXiv:2606.00002v1 Announce Type: new Abstract: Mixed-Integer Linear Programming (MILP) decision engines routinely output nominally optimal plans for high-stakes industrial systems. Yet deployment rar
arXiv:2606.00750v1 Announce Type: new Abstract: Recent advances in visual language models have enabled autonomous agents for complex reasoning, tool use, and document understanding. However, existing
arXiv:2405.01930v2 Announce Type: replace Abstract: This paper introduces OARelatedWork: a dataset for related work generation from open-access sources. It is the first large-scale multi-document summ
arXiv:2603.22999v3 Announce Type: replace Abstract: Recent advances in visual language models have enabled autonomous agents for complex reasoning, tool use, and document understanding. However, exist
arXiv:2606.02255v1 Announce Type: cross Abstract: Human annotation is the empirical foundation of much NLP research, from dataset construction to model evaluation, but papers often leave unclear who p
KYA is a framework-agnostic trust layer designed for autonomous systems that provides verifiable guarantees, addressing the need for trustworthy and transparent operation of AI agents across different
arXiv:2605.25964v1 Announce Type: new Abstract: AI Scientists have shown promising progress across multiple stages of the research pipeline, among which automatic scientific paper writing remains a fo
arXiv:2605.23951v1 Announce Type: new Abstract: The companion paper introduced a four-level verification lattice on agent-skill manifests (unverified, declared, tested, formal) and left the top level
arXiv:2510.15297v4 Announce Type: replace-cross Abstract: We introduce VERA-MH (Validation of Ethical and Responsible AI in Mental Health), an automated evaluation of the safety of AI chatbots used in
arXiv:2605.01055v1 Announce Type: cross Abstract: Object caches underpin cloud and edge services, but production workloads are heterogeneous, nonstationary, and throughput-constrained. Recent simple n
Conductor is a method for orchestrating multiple AI agents through natural language instructions, enabling coordinated multi-agent systems where a central 'conductor' agent directs specialized agents
arXiv:2604.17745v1 Announce Type: new Abstract: Recent advances in large language models have highlighted their potential to automate computational research, particularly reproducing experimental resu
Mooncake is the serving platform for Kimi developed by Moonshot AI, featuring a KVCache-centric disaggregated architecture that separates prefill and decoding clusters while leveraging underutilized C
arXiv:2604.04089v2 Announce Type: replace-cross Abstract: Large language models (LLMs) can generate code rapidly but remain unreliable for scientific algorithms whose correctness depends on structural
This Reddit thread on r/MachineLearning discusses CVPR 2026's policy requiring accepted papers to be registered under an in-person author registration, with virtual attendance still permitted if circu
arXiv:2602.11354v2 Announce Type: replace Abstract: The literature has witnessed an emerging interest in AI agents for automated assessment of scientific papers. Existing benchmarks focus primarily on
A study published in *Science* (April 2026) by researchers from the Chinese Academy of Sciences challenges the long-held view that Yellowstone's supervolcano is powered by a deep mantle plume, inst...
arXiv:2606.29872v1 Announce Type: cross Abstract: This study analyzes the novelty distribution of scholarly papers in the field of Library and Information Science (LIS) in China, with a focus on diffe
ChatGPT diagnosed 40 million people with a disease that was invented as a joke. Not a real disease. Not a misunderstood disease. A completely fictional condition with a fake name, fake papers, and fak
ANNOUNCEMENT: WE’RE SAVING SCIENCE! We’re often told that science is “self-correcting.” But that’s not really true. Science doesn’t correct itself like a thermostat adjusting the temperature in your h
arXiv:2605.19156v1 Announce Type: new Abstract: Recent auto-research systems can produce complete papers, but feasibility is not the same as quality, and the field still lacks a systematic study of ho
arXiv:2601.12369v3 Announce Type: replace Abstract: Deep Research Agents increasingly automate survey generation, yet whether they match human experts at retrieving essential papers and organizing the
arXiv:2605.10810v1 Announce Type: new Abstract: We introduce an automatically generated benchmark for predicting hidden text in technical papers. A paper supplies visible context X and a hidden contin
arXiv:2603.26791v2 Announce Type: replace-cross Abstract: Assessing a cited paper's impact is typically done by analyzing its citation context in isolation within the citing paper. While this focuses
arXiv:2604.19792v1 Announce Type: new Abstract: This paper presents OpenCLAW-P2P v6.0, a comprehensive evolution of the decentralized collective-intelligence platform in which autonomous AI agents pub
This is a Two Minute Papers episode by Dr. Károly Zsolnai-Fehér reviewing a counterintuitive NVIDIA AI research result — likely covering a technique that defies conventional expectations yet delivers
arXiv:2607.28631v1 Announce Type: new Abstract: AI Scientist systems capable of autonomous research have the potential to significantly accelerate scientific discovery. However, evaluating and compari
Hi everyone, About a month ago I publish my very first research paper on my neural network architecture called Silia. You can look at the model here: https://huggingface.co/Srijan-Srivastava/Silia-v2
arXiv:2607.03621v1 Announce Type: new Abstract: This paper presents the development and evaluation of a collaborative system for real-time reconstruction of fragmented paper documents in the context o
arXiv:2607.03709v1 Announce Type: new Abstract: Writing a literature review requires a deep understanding of the relationships among cited papers: how they build on, challenge, or offer alternative pe
This video from Two Minute Papers discusses groundbreaking research by NVIDIA that achieves a 100x speedup in physics-based character animations using AI-powered super-resolution applied to physics si
arXiv:2605.03202v1 Announce Type: new Abstract: Large language models offer a tempting solution to address the peer review crisis. This position paper argues that today's AI systems should not be used
Stealing Reasoning Traces from Proprietary LLM APIs A vanity domain name (stolen-thoughts.com) for a neat paper: Anthropic, OpenAI, and Google return encrypted chain-of-thought blocks to clients that
arXiv:2608.07204v1 Announce Type: new Abstract: Scientific claim verification over a cited paper requires predicting the claim--paper relation and identifying the paragraphs that justify that predicti
arXiv:2607.20796v1 Announce Type: new Abstract: This paper examines the question of whether artificial intelligence (AI) systems can be creative, approached from the dual perspective of a researcher t
This story is wild. The short version: OpenAI were running a cybersecurity test against an unreleased model, with the model's guardrail features turned off. Rather than solve the test, the model broke
Very cool idea to convert memory to skills. (bookmark it) Most agent memory systems retrieve past traces as passive context. MSCE turns them into executable skills instead. The training-free framework
arXiv:2607.13370v1 Announce Type: cross Abstract: This paper is an extension of a paper presented at the ICAART 2026 conference, which introduced LEA (Learning Engagement Assistant), an adaptive AI tu
arXiv:2607.12835v1 Announce Type: new Abstract: Rubric-based evaluation is a promising approach for assessing open-ended outputs from LLM-based research agents, particularly in paper reproduction, whe
arXiv:2607.10144v2 Announce Type: replace Abstract: Scientific ideation unfolds over multiple stages, including literature search, paper reading, tool use, claim checking, cross-paper synthesis, brain
Automated lint: 26 errors, 6728 warnings, 3 info
arXiv:2607.12634v1 Announce Type: new Abstract: This paper proposes a theoretical framework for understanding intelligence as a process of atomic compression and compositional reuse. We argue that cog
arXiv:2607.00738v1 Announce Type: cross Abstract: Large language models can generate polished scientific text that includes unsupported claims, allowing hallucinations to enter the archival record. As
arXiv:2512.15783v3 Announce Type: replace Abstract: This paper proposes a measurement standardisation framework that compresses expert-AI interactions into structured, comparable fields for prospectiv
Reviews and discussions for all accepted papers at ICML are made public on OpenReview after the reviewing period concludes. Authors of rejected papers may also opt-in to have their reviews and discuss
Databases have introduced new AI-powered SQL functions which take natural language instructions as input and are evaluated using LLMs. They leverage the power of LLMs to answer new kinds of queries: W
Pay attention to this one, AI devs. If you're building multi-agent systems, you're probably wiring static org charts. New research argues they should look more like a labor market. The paper introduce
What if instead of building one giant AI, we evolved a coordinator to orchestrate a diverse team of specialized AIs? 🐟 Excited to share our new paper: “TRINITY: An Evolved LLM Coordinator”, published
arXiv:2510.06708v3 Announce Type: replace-cross Abstract: Conducting systematic reviews is laborious. In the screening or study selection phase, the number of papers can be overwhelming. Recent resear
If you maintain an AGENTS.md or a CLAUDE.md, this is worth a read. (bookmark it) 288 gold-test evaluated runs across Claude Code and Codex, 17 real tasks from 3 repositories, with context-injection st
arXiv:2607.28618v1 Announce Type: new Abstract: Chemistry literature synthesis often requires assembling specific findings scattered across many publications, yet existing literature-search systems pr
arXiv:2607.27066v1 Announce Type: new Abstract: Scientific figure assessment in peer review differs fundamentally from general image quality evaluation: a figure must be visually legible, faithfully s
arXiv:2607.24538v1 Announce Type: new Abstract: In this paper, we present NEO, a unified framework providing language-guided NeRF editing for robotic manipulation. Our paper introduces (i) a language-
arXiv:2607.05743v1 Announce Type: cross Abstract: AI coding agents now read repositories, call tools, and execute shell commands with limited human oversight, and a fast-growing body of work studies w