Search: “models”

arXiv:2602.08222v2 Announce Type: replace Abstract: As post-training optimization becomes central to improving large language models, we observe a persistent saturation bottleneck: once models grow hi

tutorialsarxiv-cs-ai

9 Jun 2026

What Codex unlocks for Notion

OpenAI's Codex model enables Notion to add AI-powered capabilities to its workspace platform, allowing users to automate tasks and generate content through natural language commands. This integration

model-releasesopenai

9 Jun 2026

AdaGRPO: A Capability-Aware Adaptive Enhancement for Flow-based GRPO

arXiv:2606.06828v1 Announce Type: new Abstract: Group Relative Policy Optimization (GRPO) has demonstrated remarkable success in aligning text-to-image (T2I) flow models with human preferences. Howeve

safetyarxiv-cs-cv

Aumann-SHAP: The Geometry of Counterfactual Interaction Explanations in Machine Learning

model-releasesarxiv-cs-lg

arXiv:2603.14014v2 Announce Type: replace Abstract: We introduce Aumann-SHAP, an interaction-aware framework that decomposes counterfactual transitions by restricting the model to a local hypercube co

Building super fast experiences with Gemma just got easier. Gemma 4 MTP is now officially merged into llama.cpp. Developers can now pair MTP…

model-releasesgeorgi-gerganov--x

Gemma 4 MTP (Multi-Token Prediction) has been officially integrated into llama.cpp, enabling developers to build faster AI experiences by using the model with this inference framework. This merge allo

CoMetaPNS: Continually Meta-learning Personalized Neural Surrogates for Cardiac Electrophysiology Simulations

arXiv:2606.07488v1 Announce Type: new Abstract: Personalized virtual heart simulations face challenges in model personalization and computational cost. While neural surrogates offer state-of-the-art s

researcharxiv-cs-lg

Compute-Optimal Network Design for Echocardiography Myocardial Segmentation and Perfusion Quantification using Neural Scaling Laws

model-releasesarxiv-cs-cv

arXiv:2606.06725v1 Announce Type: cross Abstract: Myocardial perfusion quantification using contrast-enhanced ultrasound offers a bedside non-ionizing alternative to nuclear imaging modalities. Howeve

CoQuIR: A Comprehensive Benchmark for Code Quality-Aware Information Retrieval

arXiv:2506.11066v3 Announce Type: replace-cross Abstract: Code retrieval is essential in modern software development, as it boosts code reuse and accelerates debugging. However, current benchmarks pri

DaX: Learning General Pathology Representations Across Scales

arXiv:2606.06983v1 Announce Type: cross Abstract: Computational pathology requires visual representations that transfer across diverse clinical endpoints and remain robust to variation in magnificatio

Declarative Skills for AI Agents in Knowledge-Grounded Tool-Use Workflows

arXiv:2606.06923v1 Announce Type: new Abstract: We study orchestration mechanisms for tool-using AI agents in realistic customer-service workflows over an unstructured knowledge base. We argue that de

From Vision to Text: A Compact Multimodal Approach for Robust, Cross-Domain Presentation Attack Detection on ID Cards

model-releasesarxiv-cs-cv

arXiv:2606.06966v1 Announce Type: new Abstract: Cross-domain shifts challenge Presentation Attack Detection (PAD) on ID Cards, given the restricted data available due to privacy concerns. This work pr

Gemma 4 Chat Template now has preserve thinking

model-releasesr-localllama

Google added an empty thinking token to the Gemma 4 chat template, which stabilizes model output by suppressing 'ghost' thought channels that may appear even when thinking is deactivated. This update

Learning Perspectivist Social Meaning via Demographic-Conditioned Fusion Embeddings

arXiv:2606.07123v1 Announce Type: new Abstract: Social meaning in language is inherently perspectival, varying across annotator backgrounds, demographics, and ideological positions. However, most NLP

LLM-Guided Evolution for Medical Decision Pipelines

arXiv:2606.07342v1 Announce Type: new Abstract: Adapting large language models (LLMs) to clinical workflows often requires costly fine-tuning or manual prompt and pipeline engineering. We study LLM-gu

MacArena: Benchmarking Computer Use Agents on an Online macOS Environment

arXiv:2606.06560v1 Announce Type: cross Abstract: Computer-use agents (CUAs) operate graphical user interfaces (GUIs) through vision and control primitives, and their capabilities have advanced rapidl

NotebookLM’s Gemini 3.5 upgrade adds a cloud computer and help finding sources

model-releasesthe-verge-ai

Google is rolling out 'across the board' updates to NotebookLM. The AI-powered note-taking app now uses Google's upgraded Gemini 3.5 model, which will allow it to respond with 'more accurate and relia

On the Geometry of On-Policy Distillation

arXiv:2606.07082v1 Announce Type: cross Abstract: On-policy distillation (OPD) is increasingly used to improve large language model reasoning, but its training dynamics remain poorly understood. We ch

Phun-Bench: Evaluating LLMs on Phonological Understanding in Chinese

arXiv:2606.07300v1 Announce Type: new Abstract: Language is a vehicle for thought, intricately tied to sounds, symbols, and meaning. However, most large language model (LLM) research focuses on meanin

Pipeline parallelism in llama.cpp may be wasting your VRAM

model-releasesr-localllama

Pipeline parallelism in llama.cpp distributes model layers across multiple GPUs, with each GPU holding a contiguous slice of layers . However, the Reddit post likely discusses inefficiencies in how pi

RASFT: Rollout-Adaptive Supervised Fine-Tuning for Reasoning

arXiv:2606.07006v1 Announce Type: cross Abstract: Supervised fine-tuning (SFT) is a prevailing method for adapting large language models to reasoning tasks by imitating offline expert demonstrations,

safetyarxiv-cs-cl

Re-Centering Humans in LLM Personalization

arXiv:2606.06614v1 Announce Type: cross Abstract: Despite growing interest, most evaluations of large language models' (LLMs') personalization abilities have relied on synthetic data. It remains uncle

researcharxiv-cs-ai

ScenicRules: An Autonomous Driving Benchmark with Multi-Objective Specifications and Abstract Scenarios

arXiv:2602.16073v2 Announce Type: replace-cross Abstract: Developing autonomous driving systems for complex traffic environments requires balancing multiple objectives, such as avoiding collisions, ob

SEAM: Shortcut-Aware Real-Time Detection of Scripted vs. Spontaneous Speech for Interview Guardrails

model-releasesarxiv-cs-lg

arXiv:2606.06837v1 Announce Type: cross Abstract: Scripted vs spontaneous speech detection is appealing for interview guardrails, but benchmark performance can be inflated by shortcuts tied to corpus

Siri AI at WWDC 2026

model-releasessimon-willison

Given how badly burned anyone who took Apple's 2024 WWDC Apple Intelligence announcements at face value was, I'm holding to a strict 'I'll believe it when I see it' policy for everything they announce

So excited to be opening up OpenEnv to the whole community. It will now be owned by @huggingface , Meta-PyTorch, @reflection_ai , @UnslothAI…

model-releasesclem-delangue--x

So excited to be opening up OpenEnv to the whole community. It will now be owned by @huggingface , Meta-PyTorch, @reflection_ai , @UnslothAI , @modal, @PrimeIntellect , @NVIDIAAI , @mercor_ai , and @f

Sparse Subspace-to-Expert Sharing for Task-Agnostic Continual Learning

arXiv:2606.07500v1 Announce Type: cross Abstract: Continual learning in Large Language Models (LLMs) is hindered by the plasticity-stability dilemma, where acquiring new capabilities often leads to ca

Stable Reasoning, Unstable Responses: Mitigating LLM Deception via Stability Asymmetry

arXiv:2603.26846v2 Announce Type: replace-cross Abstract: As Large Language Models (LLMs) expand in capability and application scope, their trustworthiness becomes critical. A vital risk is intrinsic

safetyarxiv-cs-ai

Local Ai

The Masked Advantage: Uncovering Local-Language Access to Cultural Knowledge in LLMs

arXiv:2606.07422v1 Announce Type: cross Abstract: Large language models are increasingly used to answer culturally grounded questions across languages, yet it remains unclear whether local cultural kn

local-aiarxiv-cs-ai

The Necessity of Setting Temperature in LLM-as-a-Judge

arXiv:2603.28304v2 Announce Type: replace Abstract: Using large language models (LLMs) as judges for evaluating model outputs has emerged as an important paradigm for automated evaluation. However, th

researcharxiv-cs-cl

The Piggyback Hypothesis of Generalization: Explaining and Mitigating Emergent Misalignment

arXiv:2606.06667v1 Announce Type: new Abstract: The mechanisms behind LLMs' broad over-generalization beyond training examples remain unclear. Emergent misalignment (EM) offers a striking case study:

ThinkBooster: A Unified Framework for Seamless Test-Time Scaling of LLM Reasoning

arXiv:2606.06915v1 Announce Type: cross Abstract: Test-time compute (TTC) scaling has emerged as a powerful paradigm for improving large language model (LLM) reasoning by allocating additional compute

Uncertainty-Aware LLM-Guided Policy Shaping for Sparse-Reward Reinforcement Learning

model-releasesarxiv-cs-lg

arXiv:2606.06673v1 Announce Type: new Abstract: Sparse rewards and heterogeneous task sequences remain persistent challenges in Reinforcement Learning (RL), often resulting in slow convergence, weak g

What Do People Actually Want From AI? Mapping Preference Plurality

arXiv:2606.06674v1 Announce Type: new Abstract: Large Language Models (LLMs) are often fine-tuned through Reinforcement Learning from Human Feedback (RLHF) to align with people's preferences and value

safetyarxiv-cs-cl

When to Think Deeply: Inhibitory Deliberation for LLM Reasoning

arXiv:2606.06745v1 Announce Type: new Abstract: Reasoning Large Language Models can improve problem-solving performance through deliberative inference, but invoking slow reasoning for every input is c

Zero-Shot Embedding Drift Detection: A Lightweight Defense Against Prompt Injections in LLMs

arXiv:2601.12359v1 Announce Type: cross Abstract: Prompt injection attacks have become an increasing vulnerability for LLM applications, where adversarial prompts exploit indirect input channels such

Wasn't Krea 2 supposed to be released ?

model-releasesr-stablediffusion

Krea 2, Krea's first foundation image model built from scratch, was announced on May 12, 2026 , with a focus on aesthetics, style transfer, and creative control . Krea 2 became available to everyone s

7 Jun 2026

Agent-Orchestrated Adaptive RAG: A Comparative Study on Structured and Multi-Hop Retrieval

arXiv:2606.05658v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) enhances Large Language Models (LLMs) by grounding their responses in external knowledge, but conventional pipeli

Enhancing Software Engineering Through Closed-Loop Memory Optimization

arXiv:2606.05646v1 Announce Type: cross Abstract: Large language models (LLMs) have enabled powerful software engineering (SE) agents capable of navigating complex codebases and resolving real-world i

Evaluation of LLMs for Mathematical Formalization in Lean

arXiv:2606.05632v1 Announce Type: new Abstract: Within the past few years, the ability of Large Language Models (LLMs) to generate formal mathematical proofs has improved drastically. We provide a com

Agents

No frontier lab will own every single point on the pareto frontier around cost/latency and accuracy. Even as the pareto frontier itself adva…

No frontier lab will own every single point on the pareto frontier around cost/latency and accuracy. Even as the pareto frontier itself advances, there will always be points owned by open-weight model

agentsjerry-liu--x

SagnacAssisted Enhanced OTDR for Distributed Acoustic Sensing: A Standardized Benchmark and Engineering Evaluation Framework

arXiv:2606.05754v1 Announce Type: cross Abstract: Phase-sensitive optical time-domain reflectometry (phi-OTDR) is widely used in large-scale distributed acoustic sensing (DAS) because it provides dist

Synthetic Contrastive Reasoning for Multi-Table Q&A

arXiv:2606.05382v1 Announce Type: new Abstract: Multi-table question answering requires models to retrieve relevant evidence, link schemas, and perform compositional reasoning across relational tables

What Should Agents Say? Action-state Communication for Efficient Multi-Agent Systems

arXiv:2606.05304v1 Announce Type: new Abstract: Multi-agent systems (MAS) built on large language models are typically organized around roles, pipelines, and turn schedules, while the content that age

When Tools Fail: Benchmarking Dynamic Replanning and Anomaly Recovery in LLM Agents

arXiv:2606.05806v1 Announce Type: new Abstract: Existing benchmarks evaluate Tool-Integrated Reasoning (TIR) in LLMs on idealized ''happy paths'', largely overlooking real-world tool failures. We intr

Activation-Informed Pareto-Guided Low-Rank Compression for Efficient LLM/VLM

arXiv:2510.05544v2 Announce Type: replace Abstract: Large language models (LLM) and vision-language models (VLM) have achieved state-of-the-art performance, but they impose significant memory and comp

researcharxiv-cs-cl

Aligning Tree-Search Policies with Fixed Token Budgets in Test-Time Scaling of LLMs

arXiv:2602.09574v2 Announce Type: replace Abstract: Tree-search decoding is an effective form of test-time scaling for large language models (LLMs), but real-world deployment often imposes a fixed per

Alignment Risks from Capability-Seeking RL Training

arXiv:2602.12124v2 Announce Type: replace-cross Abstract: While most AI alignment research focuses on preventing models from generating explicitly harmful content, a more subtle risk arises from capab

safetyarxiv-cs-cl

ArcANE: Do Role-Playing Language Agents Stay in Character at the Right Time?

arXiv:2606.05553v1 Announce Type: new Abstract: Role-playing language agents (RPLAs) should play characters whose values and behavior evolve as the story progresses, not maintain a fixed persona. Exis