model releases

Pulled the trigger today and switched 100% of Lindy traffic to DeepSeek v4, churning from Anthropic models. Saves us millions of $ and we're…

model-releasesclem-delangue--x

Pulled the trigger today and switched 100% of Lindy traffic to DeepSeek v4, churning from Anthropic models. Saves us millions of $ and we're actually seeing an *increase* in performance on many core u

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QO-Bench: Diagnosing Query-Operator-Preserving Retrieval over Typed Event Tuples

arXiv:2606.04646v1 Announce Type: cross Abstract: Many real-world questions over business, legal, and scientific corpora are natural-language versions of database-style queries over records latent in

QPredSGG: Hybrid Quantum Predicate Learning for Long-Tailed Scene Graph Generation

arXiv:2606.04689v1 Announce Type: cross Abstract: Scene Graph Generation (SGG) requires relational reasoning over objects and their interactions, but performance is often limited by severe long-tail p

Quantum entanglement provides a competitive advantage in adversarial games

arXiv:2603.10289v2 Announce Type: replace-cross Abstract: Whether uniquely quantum resources confer advantages in fully classical, competitive environments remains an open question. Competitive zero-s

QuBLAST: A Framework for Quantizing Large Language Models with Block-Level Compression Approach and Activation Scaling Strategy

arXiv:2606.04620v1 Announce Type: cross Abstract: LLMs have become the state-of-the-art algorithms for solving NLP tasks. However, they typically come at huge computational and memory costs, thus maki

RAMPART: Registry-based Agentic Memory with Priority-Aware Runtime Transformation

arXiv:2606.04628v1 Announce Type: new Abstract: RAMPART is a compile-time memory model and pure in-RAM block registry for LLM-based agents. Context assembly is a programmable runtime operation where c

RAVQ-HoloNet: Rate-Adaptive Vector-Quantized Hologram Compression

arXiv:2511.21035v2 Announce Type: replace Abstract: Holography offers significant potential for AR/VR applications. However, its adoption is limited by the high demand for data compression. Existing d

Reasoning over Boundaries: Enhancing Specification Alignment via Test-time Deliberation

arXiv:2509.14760v3 Announce Type: replace Abstract: Large language models (LLMs) are increasingly applied in diverse real-world scenarios, each governed by bespoke behavioral and safety specifications

Revisiting Vul-RAG: Reproducibility and Replicability of RAG-based Vulnerability Detection with Open-Weight Models

arXiv:2606.04739v1 Announce Type: cross Abstract: Large language models (LLMs) have shown strong potential for automated software vulnerability detection, particularly in retrieval-augmented generatio

RIDE: An Open Dataset and Benchmark for Train Delay Prediction

arXiv:2606.05070v1 Announce Type: new Abstract: Train delay prediction is an important problem for both passengers and railway operators, yet progress in the field remains difficult to assess due to t

Robotics startup Generalist, which released its GEN-1 model to complete short physical tasks in April, raised 400M led by Radical Ventures at a 2B valuation (Dina Bass/Bloomberg)

Dina Bass / Bloomberg: Robotics startup Generalist, which released its GEN-1 model to complete short physical tasks in April, raised 400M led by Radical Ventures at a 2B valuation — The company raised

model-releasestechmeme

Robust Multi-view Clustering against Imperfect Information

model-releasesarxiv-cs-cv

arXiv:2606.04343v1 Announce Type: new Abstract: Real-world multi-view data always suffer from imperfect information problem, where the view-specific observations are absent (i.e., Incomplete Views, IV

Rollout-Level Advantage-Prioritized Experience Replay for GRPO

arXiv:2606.04560v1 Announce Type: cross Abstract: Reinforcement learning from verifiable rewards with GRPO is a standard approach for post-training reasoning LLMs. It remains sample inefficient. Each

Safety by narrow control has shown to fail many times. Need more transparency on the absolute frontier, and openness close behind.

model-releasesclem-delangue--x

Safety by narrow control has shown to fail many times. Need more transparency on the absolute frontier, and openness close behind. I found another API that offers claude-oceanus-v1-p the pricing and t

Safety Under Scaffolding: How Evaluation Conditions Shape Measured Safety

arXiv:2603.10044v2 Announce Type: replace-cross Abstract: A safety score earned on a benchmark need not predict how the same model behaves once it is wrapped in an agentic scaffold the benchmark never

SAM 3D: 3Dfy Anything in Images

arXiv:2511.16624v2 Announce Type: replace-cross Abstract: We present SAM 3D, a generative model for visually grounded 3D object reconstruction, predicting geometry, texture, and layout from a single i

Scaling AI Agents: A Step-by-Step Guide to Deploying ADK on GKE Autopilot

model-releasesgoogle-cloud-ai

While building AI agents locally using Google’s Agent Development Kit (ADK) is an excellent way to prototype, production-ready agents require a robust, scalable infrastructure. For developers looking

Scene-Centric Unsupervised Video Panoptic Segmentation

model-releasesarxiv-cs-cv

arXiv:2606.04925v1 Announce Type: new Abstract: Video panoptic segmentation (VPS) aims to jointly detect, segment, and track all objects while partitioning the video into semantically consistent regio

Self-Evolving Deep Research via Joint Generation and Evaluation

arXiv:2606.04507v1 Announce Type: cross Abstract: Large Language Models (LLMs) have become increasingly adopted in daily applications, with deep research standing out as a particularly important capab

Shifting the Breaking Point of Flow Matching for Multi-Instance Editing

model-releasesarxiv-cs-cv

arXiv:2602.08749v3 Announce Type: replace Abstract: Flow matching models have recently emerged as an efficient alternative to diffusion, especially for text-guided image generation and editing, offeri

Signed Dual Attention: Capturing Signed Dependencies in Time Series Forecasting

arXiv:2606.04833v1 Announce Type: cross Abstract: Initially developed for natural language processing, Transformer architectures and attention mechanisms are now central to a wide range of deep learni

SMAC-Talk: A Natural Language Extension of the StarCraft Multi-Agent Challenge for Large Language Models

arXiv:2606.04202v1 Announce Type: new Abstract: As LLMs become more widely deployed, they are increasingly expected to work alongside other AI agents rather than operating in isolation. Effective coor

SMADE-IE: Sparse Multi-Agent Framework with Evidence-Driven Debate for Zero-Shot Information Extraction

arXiv:2606.04691v1 Announce Type: new Abstract: Zero-shot information extraction (IE) with large language models (LLMs) has attracted increasing attention due to its flexibility in adapting to new sch

Solving Zebra Puzzles Using Constraint-Guided Multi-Agent Systems

arXiv:2407.03956v3 Announce Type: replace-cross Abstract: Prior research has enhanced the ability of Large Language Models (LLMs) to solve logic puzzles using techniques such as chain-of-thought promp

Sources: Anthropic has embedded around half a dozen forward-deployed engineers within the NSA to help the agency deploy Mythos for offensive cyber operations (Financial Times)

Financial Times: Sources: Anthropic has embedded around half a dozen forward-deployed engineers within the NSA to help the agency deploy Mythos for offensive cyber operations — Arrangement comes as AI

model-releasestechmeme

Speculative Thinking: Enhancing Small-Model Reasoning with Large Model Guidance at Inference Time

arXiv:2504.12329v2 Announce Type: replace-cross Abstract: Recent advances leverage post-training to enhance model reasoning performance, which typically requires costly training pipelines and still su

SPLIT-PINN: Separable Probability Learning Technique via Physics-Informed Neural Networks for High-Dimensional Probabilistic Modeling

arXiv:2606.04000v1 Announce Type: cross Abstract: We present a probabilistic modeling framework for incorporating small-scale spatial heterogeneity into macroscopic descriptions of material behavior f

StandardE2E: A Unified Framework for End-to-End Autonomous Driving Datasets

arXiv:2606.04271v1 Announce Type: cross Abstract: Autonomous driving has shifted from modular perception-prediction-planning stacks toward end-to-end (E2E) models that map sensor inputs directly to ve

StepPRM-RTL: Stepwise Process-Reward Guided LLM Fine-Tuning for Enhanced RTL Synthesis

arXiv:2606.04246v1 Announce Type: new Abstract: Automatic generation of RTL code for digital hardware designs remains challenging due to long-horizon reasoning, multi-step dependencies, and strict cor

Stepwise Reasoning Enhancement for LLMs via External Subgraph Generation

arXiv:2606.04454v1 Announce Type: new Abstract: Large language models have shown strong performance in natural language generation and downstream reasoning tasks, but they still struggle with logical

Streaming Communication in Multi-Agent Reasoning

arXiv:2606.05158v1 Announce Type: cross Abstract: Multi-agent reasoning systems adopt a 'generate-then-transfer' paradigm that forces end-to-end latency to scale linearly with pipeline depth. We intro

STRIDE: Training Data Attribution via Sparse Recovery from Subset Perturbations

arXiv:2606.05165v1 Announce Type: cross Abstract: Training Data Attribution (TDA) seeks to trace a model's predictions back to its training data. The gold standard for TDA relies on causal interventio

Structure-Aware Prediction of PROTAC-Mediated Protein Degradability via Graph Neural Networks

arXiv:2606.04021v1 Announce Type: cross Abstract: Proteolysis-targeting chimeras (PROTACs) can selectively degrade disease-causing proteins, yet predicting which targets are amenable to degradation re

Symbolic Regression for Shared Expressions: Introducing Partial Parameter Sharing

arXiv:2601.04051v3 Announce Type: replace Abstract: Symbolic regression aims to find symbolic expressions that describe datasets. Due to its inherent interpretability, symbolic regression (SR) is a po

SymTRELLIS: Symmetry-Enforced Voxel Latents for 3D Generation

arXiv:2606.04108v1 Announce Type: cross Abstract: Single-view 3D generative models have achieved impressive visual quality, yet they are not designed to satisfy structural or functional requirements,

TaDA: Calibrated Probe Gating for Task-Domain LoRA Merging

arXiv:2606.05016v1 Announce Type: new Abstract: Combining a task LoRA adapter with a domain LoRA adapter into a single unified model is a practical yet largely unexplored challenge. Existing methods t

Test-Time Compute Scaling for ASR with Depth-Conditioned Looped Transformers

arXiv:2606.04678v1 Announce Type: new Abstract: End-to-end ASR systems typically use fixed-depth acoustic encoders at inference, making it difficult to trade additional test-time computation for impro

That's a badass title, and it's true! Every day, it gets harder and harder to create tests that AI models can't beat. Reality is humanity's …

That's a badass title, and it's true! Every day, it gets harder and harder to create tests that AI models can't beat. Reality is humanity's real last exam. Andon Labs' Real-World AI Evals: Claude call

model-releasesswyx--x

The Canadian AI strategy unveiled today advocates for the development of technology that is safe, ethical, trustworthy, and that benefits so…

model-releasesyoshua-bengio--x

The Canadian AI strategy unveiled today advocates for the development of technology that is safe, ethical, trustworthy, and that benefits society as a whole—these are exactly the principles that need

The capabilities of Claude Code and Codex have expanded a lot in recent months, they added many ways to approach work (subagents, skills, go…

model-releasesethan-mollick--x

The capabilities of Claude Code and Codex have expanded a lot in recent months, they added many ways to approach work (subagents, skills, goal, workflows, plugins, etc). Given the AI labs can use thei

The Meta-Agent Challenge: Are Current Agents Capable of Autonomous Agent Development?

arXiv:2606.04455v1 Announce Type: new Abstract: Current AI benchmarks evaluate agents on task execution within human-designed workflows. These evaluations fundamentally fail to measure a critical next

The new memory system will keep track of important details automatically. If you prefer the legacy saved memories experience, you can switch…

The new memory system will keep track of important details automatically. If you prefer the legacy saved memories experience, you can switch back in settings. The new memory system is rolling out to P

model-releasesopenai--x

The Saturation Trap and the Subjectivity of Intervention Timing: Why Affect-Based Triggers and LLM Judges Fail to Time Interventions on Autonomous Agents

arXiv:2606.04296v1 Announce Type: new Abstract: As autonomous AI agents move from conversational systems to long-horizon software execution, runtime safety layers that decide when to interrupt an agen

The Variance Brain Foundation Models Forgot: Third-Order Statistics Predict Cognition Where Billion-Parameter Models Fail

arXiv:2606.04010v1 Announce Type: cross Abstract: Brain foundation models (BFMs) are self-supervised Transformers pretrained on fMRI data. We posit that these models should capture each subject's cogn

Thinking Through Signs: PEEL as a Semiotic Scaffolding for Epistemically Accountable AI-Enabled Research

arXiv:2606.04152v1 Announce Type: new Abstract: Large language models are reshaping research practice while quietly eroding researchers epistemic accountability. This commentary introduces PEEL - Prot

Today I'm launching a new project called SynthTraces 🔥 It is a minimal codebase to generate synthetic coding agent session traces using Pi …

model-releasesclem-delangue--x

Today I'm launching a new project called SynthTraces 🔥 It is a minimal codebase to generate synthetic coding agent session traces using Pi (from @badlogicgames) I wanted a large number of coding-agent

Toward a Generalized Defense Across Sparse, Continuous, and Structured Parameter Attacks

arXiv:2606.04317v1 Announce Type: cross Abstract: Deep neural networks are increasingly deployed across heterogeneous and partially untrusted environments, where models are distributed through cloud s

Toward Pre-Deployment Assurance for Enterprise AI Agents: Ontology-Grounded Simulation and Trust Certification

arXiv:2606.04037v1 Announce Type: new Abstract: Pre-deployment verification of enterprise artificial intelligence (AI) agents remains a critical gap between large language model (LLM) capability bench