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Q&A with Scott Wu, CEO of Cognition, which hit a $445M revenue run rate in its first 18 months, on his math competition roots, the Devin AI coding agent, more (Jeremy Stern/Colossus)

Jeremy Stern / Colossus: Q&A with Scott Wu, CEO of Cognition, which hit a $445M revenue run rate in its first 18 months, on his math competition roots, the Devin AI coding agent, more — An afternoon w

agentstechmeme

Content type

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Tools

Qdrant 1.18 - TurboQuant

DGX agent

Qdrant 1.18.0 is out! Let’s look at the main features for this version: TurboQuant: A new quantization method that, at twice the compression ratio of scalar quantization, delivers similar recall and s

toolsqdrant

11 May 2026

QuadNorm: Resolution-Robust Normalization for Neural Operators

arXiv:2605.07375v1 Announce Type: new Abstract: Normalization layers in neural operators usually compute statistics by uniformly averaging discrete grid values, making the normalization itself discret

researcharxiv-cs-lg

Quality-Conditioned Agreement in Automated Short Answer Scoring: Mid-Range Degradation and the Impact of Task-Specific Adaptation

arXiv:2605.07647v1 Announce Type: cross Abstract: Automated short answer scoring (ASAS) is shifting from discriminative, fine-tuned models to large language models (LLMs) used in few-shot settings. Th

Query-efficient model evaluation using cached responses

arXiv:2605.07096v1 Announce Type: cross Abstract: Evaluating a new model on an existing benchmark is often necessary to understand its behavior before deployment. For modern evaluation frameworks, gen

Quiq extends its AI agent platform into voice as enterprise rollouts move past pilots

Artificial intelligence customer service platform provider Quiq Inc. today launched a new voice product and refreshed its brand, betting that customer experience teams are ready to move beyond isolate

agentssiliconangle

Quotient Semivalues for False-Name-Resistant Data Attribution

model-releasesarxiv-cs-lg

arXiv:2605.07663v1 Announce Type: cross Abstract: Data valuation methods allocate payments and audit training data's contribution to machine-learning pipelines; however, they often assume passive cont

Quoting James Shore

Your AI coding agent, the one you use to write code, needs to reduce your maintenance costs. Not by a little bit, either. You write code twice as quick now? Better hope you’ve halved your maintenance

agentssimon-willison

Qwen 3.6 Plus by @Alibaba_Qwen is now FREE for a limited time on Nous Portal! Nous Portal is one easy subscription that gives you access to …

model-releasesnous-research--x

Qwen 3.6 Plus by @Alibaba_Qwen is now FREE for a limited time on Nous Portal! Nous Portal is one easy subscription that gives you access to 300+ models, exclusive discounts, and bundles your tokens an

Qwen3-VL-Seg: Unlocking Open-World Referring Segmentation with Vision-Language Grounding

arXiv:2605.07141v1 Announce Type: cross Abstract: Open-world referring segmentation requires grounding unconstrained language expressions to precise pixel-level regions. Existing multimodal large lang

R-GTD: A Geometric Analysis of Gradient Temporal-Difference Learning in Singular Regimes

arXiv:2601.20599v2 Announce Type: replace-cross Abstract: Gradient temporal-difference (GTD) learning algorithms are widely used for off-policy policy evaluation with function approximation. However,

R^3L: Reasoning 3D Layouts from Relative Spatial Relations

arXiv:2605.06758v1 Announce Type: cross Abstract: Relative spatial relations provide a compact representation of spatial structure and are fundamental to relative spatial reasoning in 3D layout genera

researcharxiv-cs-ai

Radiologist-Guided Causal Concept Bottleneck Models for Chest X-Ray Interpretation

arXiv:2605.07785v1 Announce Type: new Abstract: Concept Bottleneck Models (CBMs) in medical imaging aim to improve model interpretability by predicting intermediate clinical concepts before final diag

safetyarxiv-cs-cv

Randomness is sometimes necessary for coordination

arXiv:2605.06825v1 Announce Type: new Abstract: Full parameter sharing is standard in cooperative multi-agent reinforcement learning (MARL) for homogeneous agents. Under permutation-symmetric observat

Hardware

RateQuant: Optimal Mixed-Precision KV Cache Quantization via Rate-Distortion Theory

arXiv:2605.06675v1 Announce Type: cross Abstract: Large language models cache all previously computed key-value (KV) pairs during generation, and this KV cache grows linearly with sequence length, mak

hardwarearxiv-cs-cl

RCoT-Seg: Reinforced Chain-of-Thought for Video Reasoning and Segmentation

model-releasesarxiv-cs-cv

arXiv:2605.07334v1 Announce Type: new Abstract: Video Reasoning Segmentation (VRS) aims to segment target objects in videos based on implicit instructions that convey human intent and temporal logic.

Local Ai

Reachy Mini ready to go! Audio on 🔉 Cleary I'll connect it to Local AI services and to my Hermes Agent really soon 💪

Clem Delangue announced the Reachy Mini robot is operational with audio capabilities enabled, with plans to integrate it with local AI services and a Hermes Agent in the near future. This indicates pr

local-aiclem-delangue--x

Read the full blog: https://www.together.ai/blog/serving-deepseek-v4-why-million-token-context-is-an-inference-systems-problem# Watch the fu…

model-releasestogether-ai--x

Read the full blog: https://www.together.ai/blog/serving-deepseek-v4-why-million-token-context-is-an-inference-systems-problem# Watch the full webinar on DeepSeek v4: https://www.youtube.com/watch?v=D

Real-IAD MVN: A Multi-View Normal Vector Dataset and Benchmark for High-Fidelity Industrial Anomaly Detection

model-releasesarxiv-cs-cv

arXiv:2605.07149v1 Announce Type: new Abstract: Industrial Anomaly Detection (IAD) is critical for quality control, but existing methods struggle with subtle, geometric defects. Standard 2D (RGB) imag

real time model streaming audio/video/text in and out with tool use

real time model streaming audio/video/text in and out with tool use People talk, listen, watch, think, and collaborate at the same time, in real time. We've designed an AI that works with people the s

agentsyohei-nakajima--x

Applications

Really doubt what Hinton says here. Self-play for games like Go is not like the open-ended real world.

applicationsgary-marcus--x

Really doubt what Hinton says here. Self-play for games like Go is not like the open-ended real world. Geoffrey Hinton says AI systems can keep improving when they are not limited by human data Like A

Reason to Play: Behavioral and Brain Alignment Between Frontier LRMs and Human Game Learners

arXiv:2605.08019v1 Announce Type: new Abstract: Humans rapidly learn abstract knowledge when encountering novel environments and flexibly deploy this knowledge to guide efficient and intelligent actio

ReasonEdit: Towards Interpretable Image Editing Evaluation via Reinforcement Learning

arXiv:2605.07477v1 Announce Type: new Abstract: Recent text-guided image editing (TIE) models have achieved remarkable progress, however, many edited results still suffer from artifacts, unintended mo

safetyarxiv-cs-cv

ReasonSTL: Bridging Natural Language and Signal Temporal Logic via Tool-Augmented Process-Rewarded Learning

arXiv:2605.06483v2 Announce Type: replace Abstract: Signal Temporal Logic (STL) is an expressive formal language for specifying spatio-temporal requirements over real-valued, real-time signals. It has

Rebalancing gradient to improve self-supervised co-training of depth, odometry and optical flow predictions

arXiv:2605.07945v1 Announce Type: new Abstract: We present CoopNet, an approach that improves the cooperation of co-trained networks by dynamically adapting the apportionment of gradient, to ensure eq

researcharxiv-cs-cv

Receipts: https://open.substack.com/pub/garymarcus/p/deconstructing-geoffrey-hintons-weakest?r=8tdk6&utm_medium=ios

Gary Marcus analyzes and critiques Geoffrey Hinton's arguments regarding weaknesses in deep learning and artificial neural networks. The article likely examines specific technical or conceptual claims

safetygary-marcus--x

ReCLIP++: Learn to Rectify the Bias of CLIP for Unsupervised Semantic Segmentation

arXiv:2408.06747v4 Announce Type: replace Abstract: Recent works utilize CLIP to perform the challenging unsupervised semantic segmentation task where only images without annotations are available. Ho

safetyarxiv-cs-cv

Applications

RECON: Robust symmetry discovery via Explicit Canonical Orientation Normalization

arXiv:2505.13289v5 Announce Type: replace-cross Abstract: Real world data often exhibits unknown, instance-specific symmetries that rarely exactly match a transformation group G fixed a priori. Class-

applicationsarxiv-cs-cv

RedDiffuser: Auditing Multimodal Safety Failures in Vision-Language Models via Reinforced Diffusion

model-releasesarxiv-cs-cv

arXiv:2503.06223v5 Announce Type: replace Abstract: Large Vision-Language Models (VLMs) are increasingly deployed in open-ended environments, where ensuring reliable safety under multimodal inputs is

Reflections and New Directions for Human-Centered Large Language Models

arXiv:2605.06901v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly shaping the private and professional lives of users, with numerous applications in business, education, fi

safetyarxiv-cs-cl

Local Ai

Reformulating KV Cache Eviction Problem for Long-Context LLM Inference

arXiv:2605.07234v1 Announce Type: cross Abstract: Large language models (LLMs) support long-context inference but suffer from substantial memory and runtime overhead due to Key-Value (KV) Cache growth

local-aiarxiv-cs-ai

Region4Web: Rethinking Observation Space Granularity for Web Agents

arXiv:2605.07134v1 Announce Type: cross Abstract: Web agents perceive web pages through an observation space, yet its granularity has remained an underexamined design choice. Existing work treats obse

Regret-Oracle Complexity Tradeoffs in Agnostic Online Learning

arXiv:2605.07155v1 Announce Type: new Abstract: Agnostic online learning is classically solved via a reduction to the realizable setting, utilizing Littlestone's Standard Optimal Algorithm (SOA) as a

researcharxiv-cs-lg

Regulating Branch Parallelism in LLM Serving

arXiv:2605.06914v1 Announce Type: cross Abstract: Recent methods expose intra-request parallelism in LLM outputs, allowing independent branches to decode concurrently. Existing serving systems execute

researcharxiv-cs-ai

Reinforcement Learning for Exponential Utility: Algorithms and Convergence in Discounted MDPs

arXiv:2605.08053v1 Announce Type: new Abstract: Reinforcement learning (RL) for exponential-utility optimization in discounted Markov decision processes (MDPs) lacks principled value-based algorithms.

safetyarxiv-cs-lg

RelAgent: LLM Agents as Data Scientists for Relational Learning

arXiv:2605.07840v1 Announce Type: new Abstract: Relational learning is a challenging problem that has motivated a wide range of approaches, including graph-based models (e.g., graph neural networks, g

agentsarxiv-cs-lg

Relay Buffer Independent Communication over Pooled HBM for Efficient MoE Inference on Ascend

arXiv:2605.06055v2 Announce Type: replace-cross Abstract: Mixture-of-Experts (MoE) inference requires large-scale token exchange across devices, making dispatch and combine major bottlenecks in both p

researcharxiv-cs-lg

Reliable Chain-of-Thought via Prefix Consistency

arXiv:2605.07654v1 Announce Type: cross Abstract: Large Language Models often improve accuracy on reasoning tasks by sampling multiple Chain-of-Thought (CoT) traces and aggregating them with majority

researcharxiv-cs-cl

RELO: Reinforcement Learning to Localize for Visual Object Tracking

arXiv:2605.07379v1 Announce Type: cross Abstract: Conventional visual object trackers localize targets using handcrafted spatial priors, often in the form of heatmaps. Such priors provide only surroga

Hardware

Render, Don't Decode: Weight-Space World Models with Latent Structural Disentanglement

arXiv:2605.06298v2 Announce Type: replace-cross Abstract: Training world models on vast quantities of unlabelled videos is a critical step toward fully autonomous intelligence. However, the prevailing

hardwarearxiv-cs-ai

Rep2Text: Decoding Full Text from a Single LLM Token Representation

arXiv:2511.06571v3 Announce Type: replace-cross Abstract: Large language models (LLMs) have achieved remarkable progress across diverse tasks, yet their internal mechanisms remain largely opaque. In t

Repeated Deceptive Path Planning against Learnable Observer

arXiv:2605.07174v1 Announce Type: new Abstract: We study the problem of deceptive path planning (DPP), where an agent aims to conceal its true destination from external observers. While existing work

Replicating Human Motivated Reasoning Studies with LLMs

arXiv:2601.16130v2 Announce Type: replace-cross Abstract: Motivated reasoning - the idea that individuals processing information may be motivated to either arrive at accurate beliefs or arrive at desi

researcharxiv-cs-ai

reply to Hinton’s reply to me, for additional context:

reply to Hinton’s reply to me, for additional context: Dear @geoffreyhinton, I literally never said that AI systems “JUST regurgitate”; that’s plainly false. I don’t believe it, and I didn’t say it. (

safetygary-marcus--x

Industry

Report: AI chipmaker Cerebras to increase IPO price target amid surging investor demand

Artificial intelligence chipmaker Cerebras Systems Inc. is expected to increase the size and price of its initial public offering later today as investor demand for access to its shares continues to r

industrysiliconangle

ReSeek: A Self-Correcting Framework for Search Agents with Instructive Rewards

model-releasesarxiv-cs-cl

arXiv:2510.00568v3 Announce Type: replace Abstract: Search agents powered by Large Language Models (LLMs) have demonstrated significant potential in tackling knowledge-intensive tasks. Reinforcement l

Resource-Element Energy Difference for Noncoherent Over-the-Air Federated Learning

arXiv:2605.07263v1 Announce Type: cross Abstract: Over-the-air federated learning (OTA-FL) reduces uplink latency by exploiting waveform superposition, but conventional analog aggregation schemes typi

Response-G1: Explicit Scene Graph Modeling for Proactive Streaming Video Understanding

arXiv:2605.07575v1 Announce Type: cross Abstract: Proactive streaming video understanding requires Video-LLMs to decide when to respond as a video unfolds, a task where existing methods often fall sho