model releases

iNaturalist Sightings

model-releasessimon-willison

Tool: iNaturalist Sightings I wanted to see my iNaturalist observations - across two separate accounts - grouped by when they occurred. I'm camping this weekend so I built this entirely on my phone us

Instruction Complexity Induces Positional Collapse in Adversarial LLM Evaluation

arXiv:2604.27249v1 Announce Type: cross Abstract: When instructed to underperform on multiple-choice evaluations, do language models engage with question content or fall back on positional shortcuts?

model-releasesarxiv-cs-ai

1 May 2026

Intent2Tx: Benchmarking LLMs for Translating Natural Language Intents into Ethereum Transactions

arXiv:2604.27763v1 Announce Type: new Abstract: The emergence of Large Language Models (LLMs) offers a transformative interface for Web3, yet existing benchmarks fail to capture the complexity of tran

InteractWeb-Bench: Can Multimodal Agent Escape Blind Execution in Interactive Website Generation?

arXiv:2604.27419v1 Announce Type: new Abstract: With the advancement of multimodal large language models (MLLMs) and coding agents, the website development has shifted from manual programming to agent

Iterative Definition Refinement for Zero-Shot Classification via LLM-Based Semantic Prototype Optimization

arXiv:2604.27335v1 Announce Type: new Abstract: Web filtering systems rely on accurate web content classification to block cyber threats, prevent data exfiltration, and ensure compliance. However, cla

Iterative Multimodal Retrieval-Augmented Generation for Medical Question Answering

arXiv:2604.27724v1 Announce Type: new Abstract: Medical retrieval-augmented generation (RAG) systems typically operate on text chunks extracted from biomedical literature, discarding the rich visual c

ITS-Mina: A Harris Hawks Optimization-Based All-MLP Framework with Iterative Refinement and External Attention for Multivariate Time Series Forecasting

arXiv:2604.27981v1 Announce Type: cross Abstract: Multivariate time series forecasting plays a pivotal role in numerous real-world applications, including financial analysis, energy management, and tr

JI-ADF: Joint-Individual Learning with Adaptive Decision Fusion for Multimodal Skin Lesion Classification

arXiv:2604.27343v1 Announce Type: new Abstract: Skin lesion classification is essential for early dermatological diagnosis, yet many existing computer-aided systems rely primarily on dermoscopic image

Judge, Then Drive: A Critic-Centric Vision Language Action Framework for Autonomous Driving

arXiv:2604.27366v1 Announce Type: new Abstract: Recent advances in vision language action (VLA) models have shown remarkable potential for autonomous driving by directly mapping multimodal inputs to c

K2MUSE: A human lower-limb multimodal walking dataset spanning task and acquisition variability for rehabilitation robotics

arXiv:2504.14602v2 Announce Type: replace-cross Abstract: The natural interaction and control performance of lower limb rehabilitation robots are closely linked to biomechanical information from vario

KellyBench: A Benchmark for Long-Horizon Sequential Decision Making

arXiv:2604.27865v1 Announce Type: new Abstract: Language models are saturating benchmarks for procedural tasks with narrow objectives. But they are increasingly being deployed in long-horizon, non-sta

Language Models Refine Mechanical Linkage Designs Through Symbolic Reflection and Modular Optimisation

arXiv:2604.27962v1 Announce Type: new Abstract: Designing mechanical linkages involves combinatorial topology selection and continuous parameter fitting. We show that language models can systematicall

LaST-R1: Reinforcing Action via Adaptive Physical Latent Reasoning for VLA Models

arXiv:2604.28192v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models have increasingly incorporated reasoning mechanisms for complex robotic manipulation. However, existing approaches

Learning Generalizable Multimodal Representations for Software Vulnerability Detection

arXiv:2604.25711v2 Announce Type: replace-cross Abstract: Source code and its accompanying comments are complementary yet naturally aligned modalities-code encodes structural logic while comments capt

Learning Rate Engineering: From Coarse Single Parameter to Layered Evolution

arXiv:2604.27295v1 Announce Type: new Abstract: Learning rate scheduling has evolved from the single global fixed rate of early SGD to sophisticated layer-wise adaptive strategies. We systematize this

Learning to Forget: Continual Learning with Adaptive Weight Decay

arXiv:2604.27063v1 Announce Type: new Abstract: Continual learning agents with finite capacity must balance acquiring new knowledge with retaining the old. This requires controlled forgetting of knowl

Lightweight Distillation of SAM 3 and DINOv3 for Edge-Deployable Individual-Level Livestock Monitoring and Longitudinal Visual Analytics

arXiv:2604.27128v1 Announce Type: cross Abstract: Foundation-model pipelines for individual-level livestock monitoring -- combining open-vocabulary detection, promptable video segmentation, and self-s

LLM-Guided Runtime Parameter Optimization for Energy-Efficient Model Inference

arXiv:2604.27032v1 Announce Type: cross Abstract: Large Language Models (LLMs) have become an integral part of many real-world workflows. However, LLMs consume a lot of energy, which becomes a large c

Local AI is about to be competitive. I will do everything in my power to make it better than Claude desktop/claude code by end of year.

model-releasesclem-delangue--x

Clem Delangue expresses commitment to advancing local AI models to compete with Anthropic's Claude Desktop and Claude Code offerings by year-end. The statement suggests focus on improving local AI cap

Lost in Space? Vision-Language Models Struggle with Relative Camera Pose Estimation

arXiv:2601.22228v2 Announce Type: replace-cross Abstract: We study whether vision-language models (VLMs) can solve relative camera pose estimation (RCPE) from image pairs, a direct test of multi-view

Low Rank Adaptation for Adversarial Perturbation

arXiv:2604.27487v1 Announce Type: new Abstract: Low-Rank Adaptation (LoRA), which leverages the insight that model updates typically reside in a low-dimensional space, has significantly improved the t

M-DaQ: Retrieving Samples with Multilingual Diversity and Quality for Instruction Fine-Tuning Datasets

arXiv:2509.15549v2 Announce Type: replace Abstract: Multilingual instruction fine-tuning (IFT) empowers large language models to generalize across diverse linguistic and cultural contexts; however, hi

MAEO: Multiobjective Animorphic Ensemble Optimization for Scalable Large-scale Engineering Applications

arXiv:2604.26973v1 Announce Type: cross Abstract: Multiobjective optimization remains challenging for many scientific and engineering problems due to the need to balance convergence, diversity, and co

Make sure to read the blog post for a detailed analysis of frontier model failure modes: https://arcprize.org/blog/arc-agi-3-gpt-5-5-opus-4-…

model-releasesfrancois-chollet--x

Francois Chollet shared a blog post analyzing failure modes of frontier AI models, specifically examining performance on the ARC (Abstraction and Reasoning Corpus) AGI benchmark with models including

Mapping the Phase Diagram of the Vicsek Model with Machine Learning

arXiv:2604.28167v1 Announce Type: cross Abstract: In this study, we use machine learning to classify and interpolate the phase structure of the Vicsek flocking model across the three-dimensional param

Math Education Digital Shadows for facilitating learning with LLMs: Math performance, anxiety and confidence in simulated students and AIs

arXiv:2604.27618v1 Announce Type: new Abstract: To enhance LLMs' impact on math education, we need data on their mathematical prowess and biases across prompts. To fill this gap, we introduce MEDS (Ma

MCPHunt: An Evaluation Framework for Cross-Boundary Data Propagation in Multi-Server MCP Agents

arXiv:2604.27819v1 Announce Type: new Abstract: Multi-server MCP agents create an information-flow control problem: faithful tool composition can turn individually benign read/write permissions into c

Measurement Risk in Supervised Financial NLP: Rubric and Metric Sensitivity on JF-ICR

arXiv:2604.27374v1 Announce Type: new Abstract: As LLMs become credible readers of earnings calls, investor-relations Q&A, guidance, and disclosure language, supervised financial NLP benchmarks increa

MiniCPM-o 4.5: Towards Real-Time Full-Duplex Omni-Modal Interaction

arXiv:2604.27393v1 Announce Type: new Abstract: Recent progress in multimodal large language models (MLLMs) has brought AI capabilities from static offline data processing to real-time streaming inter

Models Recall What They Violate: Constraint Adherence in Multi-Turn LLM Ideation

arXiv:2604.28031v1 Announce Type: new Abstract: When researchers iteratively refine ideas with large language models, do the models preserve fidelity to the original objective? We introduce DriftBench

Monitoring Neural Training with Topology: A Footprint-Predictable Collapse Index

arXiv:2604.26984v1 Announce Type: new Abstract: Representational collapse, where embeddings become anisotropic and lose multi-scale structure, can erode downstream performance long before performance

MultiBLiMP 1.0: A Massively Multilingual Benchmark of Linguistic Minimal Pairs

arXiv:2504.02768v4 Announce Type: replace Abstract: We introduce MultiBLiMP 1.0, a massively multilingual benchmark of linguistic minimal pairs, covering 101 languages and 2 types of subject-verb agre

NanoKnow: How to Know What Your Language Model Knows

arXiv:2602.20122v2 Announce Type: replace-cross Abstract: How do large language models (LLMs) know what they know? Answering this question has been difficult because pre-training data is often a 'blac

NashPG: A Policy Gradient Method with Iteratively Refined Regularization for Finding Nash Equilibria

arXiv:2510.18183v2 Announce Type: replace Abstract: Finding Nash equilibria in two-player zero-sum imperfect-information games remains a central challenge in multi-agent reinforcement learning. Recent

NeocorRAG: Less Irrelevant Information, More Explicit Evidence, and More Effective Recall via Evidence Chains

arXiv:2604.27852v1 Announce Type: cross Abstract: Although precise recall is a core objective in Retrieval-Augmented Generation (RAG), a critical oversight persists in the field: improvements in retri

ObjectGraph: From Document Injection to Knowledge Traversal -- A Native File Format for the Agentic Era

arXiv:2604.27820v1 Announce Type: new Abstract: Every document format in existence was designed for a human reader moving linearly through text. Autonomous LLM agents do not read - they retrieve. This

📢 Official Announcement: Qwen Partners with Fireworks AI to Accelerate Access to Qwen Family Models We are pleased to announce a strategic …

📢 Official Announcement: Qwen Partners with Fireworks AI to Accelerate Access to Qwen Family Models We are pleased to announce a strategic partnership between Qwen and Fireworks AI to deliver optimize

model-releasesqwen--x

On 5/5 @realDanFu and team will discuss DSV4’s hybrid attention and KV cache efficiency, should be a great session!

model-releasestogether-ai--x

On 5/5 @realDanFu and team will discuss DSV4’s hybrid attention and KV cache efficiency, should be a great session! Join us Tue 5/5: #DeepSeek-V4's hybrid attention + sparse MoE reduces KV cache up to

Once again IP thieves accusing other IP thieves of IP thievery! The nerve!

model-releasesgary-marcus--x

Once again IP thieves accusing other IP thieves of IP thievery! The nerve! @ChrisRMcGuire Anthropic claimed OpenAI violated their terms of service by using their API (I suspect they would call it “dis

One week since the launch of GPT-5.5, and it’s already our strongest model launch yet. API revenue is growing more than 2x faster than any p…

One week since the launch of GPT-5.5, and it’s already our strongest model launch yet. API revenue is growing more than 2x faster than any prior release, while Codex doubled revenue in under seven day

model-releasesopenai--x

OpenClassGen: A Large-Scale Corpus of Real-World Python Classes for LLM Research

arXiv:2504.15564v3 Announce Type: replace-cross Abstract: Existing class-level code generation datasets are either synthetic (ClassEval: 100 classes) or insufficient in scale for modern training needs

OR-VSKC: Resolving Visual-Semantic Knowledge Conflicts in Operating Rooms with Synthetic Data-Guided Alignment

arXiv:2506.22500v2 Announce Type: replace-cross Abstract: Automated identification of surgical safety risks is critical for improving patient outcomes; however, Multimodal Large Language Models (MLLMs

ORFS-agent: Tool-Using Agents for Chip Design Optimization

arXiv:2506.08332v3 Announce Type: replace Abstract: Machine learning has been widely used to optimize complex engineering workflows across numerous domains. In integrated circuit design, modern flows

Our CEO @jerryjliu0 in @VentureBeat , on what's actually changing in the LLM stack: 'We've really identified that there's a core set of data…

model-releasesjerry-liu--x

Our CEO @jerryjliu0 in @VentureBeat , on what's actually changing in the LLM stack: 'We've really identified that there's a core set of data that has been locked up in all these file format containers

Parameter-Efficient Architectural Modifications for Translation-Invariant CNNs

arXiv:2604.27870v1 Announce Type: new Abstract: Convolutional Neural Networks (CNNs) are widely assumed to be translation-invariant, yet standard architectures exhibit a startling fragility: even a si

People-Centred Medical Image Analysis

arXiv:2604.26991v1 Announce Type: cross Abstract: Recent advances in data-centric medical AI have produced highly accurate diagnostic systems, but the emphasis on data curation and performance metrics

Perturbation Probing: A Two-Pass-per-Prompt Diagnostic for FFN Behavioral Circuits in Aligned LLMs

arXiv:2604.27401v1 Announce Type: new Abstract: Perturbation probing generates task-specific causal hypotheses for FFN neurons in large language models using two forward passes per prompt and no backp

PhyCo: Learning Controllable Physical Priors for Generative Motion

arXiv:2604.28169v1 Announce Type: cross Abstract: Modern video diffusion models excel at appearance synthesis but still struggle with physical consistency: objects drift, collisions lack realistic reb