Search: “model-releases”

ParseBench is now also available on Papers with Code! Find it here: https://paperswithcode.co/benchmark/parsebench

model-releasesjerry-liu--x

ParseBench is now also available on Papers with Code! Find it here: https://paperswithcode.co/benchmark/parsebench We benchmarked Mistral OCR against other frontier and open-weight models on ParseBenc

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Model Releases

PatternGSL: A Structured Specification Language for Template-Free and Simulation-Ready 3D Garments

DGX agent

arXiv:2606.24564v1 Announce Type: new Abstract: Reconstructing realistic, physically plausible garments from a single image remains a fundamental challenge. Template-free methods capture surface geome

model-releasesarxiv-cs-cv

24 Jun 2026

PDS Joint: A Parametric Double-Spiral Joint Tailored for Dexterous Hands

model-releasesarxiv-cs-ro

arXiv:2606.24377v1 Announce Type: new Abstract: Compliant joints can embed safety and adaptability into dexterous hands, but achieving large-stroke anthropomorphic motion while maintaining joint-speci

PEARL: Self-Evolving Assistant for Time Management with Reinforcement Learning

arXiv:2601.11957v4 Announce Type: replace Abstract: Overlapping calendar invitations force busy professionals to repeatedly decide which meetings to attend, reschedule, or decline. We refer to this pr

Performance and Interpretability of Convolutional, Transformer, and Hybrid Deep Learning Models in Colorectal Histology Classification

arXiv:2606.23744v1 Announce Type: cross Abstract: Deep learning has become an important tool in computational pathology, enabling automated analysis of histopathological images. While convolutional ne

PETRA: Transforming Web Text for Petroleum-Engineering Domain Adaptation

arXiv:2606.24346v1 Announce Type: cross Abstract: Petroleum-engineering search exposes a supervision gap for strong general retrievers: relevant evidence exists in public web text, but domain relevanc

Point-Voxel Absorbing Graph Representation Learning for Event Stream based Recognition

arXiv:2306.05239v3 Announce Type: replace Abstract: Sampled point and voxel methods are usually employed to downsample the dense events into sparse ones. After that, one popular way is to leverage a g

Poster: Exploring the Limits of Audio-Based Detection of Turkish Phone Call Scams

arXiv:2606.24523v1 Announce Type: cross Abstract: Scam phone calls exploit vulnerable communities worldwide, yet research on detection has focused almost exclusively on English and other high-resource

Privacy-Preserving RAG via Multi-Agent Semantic Rewriting: Achieving Confidentiality Without Compromising Contextual Fidelity

arXiv:2606.24623v1 Announce Type: cross Abstract: Retrieval-Augmented Generation enhances large language models by incorporating external knowledge, but deploying it in sensitive scenarios risks priva

Project Ariadne: Prompt-Conditioned Route Generation for Synthesis Planning

arXiv:2606.24184v1 Announce Type: new Abstract: Retrosynthetic planning seeks to connect a target molecule to commercially available starting materials through a multistep route. Classical planners co

PROTECT-90: A Fault Dataset for Power System Protection

arXiv:2606.24298v1 Announce Type: cross Abstract: The increasing interest in data-driven methods for power system protection is accompanied by a lack of standardized, publicly available high-voltage w

Quantum ring all-reduce: communication and privacy advantages for distributed learning

arXiv:2606.20344v2 Announce Type: replace-cross Abstract: Machine learning models have scaled to unprecedented sizes, making training across distributed devices the de facto standard in the field. In

QuechuaTok: Morphological Boundary Accuracy as a Necessary Metric for Tokenizer Evaluation in Agglutinative Low-Resource Languages

arXiv:2606.23943v1 Announce Type: new Abstract: Tokenization is a foundational step in NLP pipelines, yet standard evaluation metrics such as fertility rate fail to capture morphological correctness f

Qwen-AgentWorld: Language World Models for General Agents

arXiv:2606.24597v1 Announce Type: new Abstract: A world model predicts environment dynamics based on current observations and actions, serving as a core cognitive mechanism for reasoning and planning.

Random Rule Forest (RRF): Interpretable and Manageable Ensembles of LLM-Generated Questions for Predicting Success from Unstructured Data

arXiv:2505.24622v3 Announce Type: replace Abstract: Many high-stakes screening tasks require predicting rare outcomes from unstructured text, where errors are costly and decisions must be auditable. W

Rapid FinFET Modelling Using an Autoencoder

arXiv:2606.24046v1 Announce Type: cross Abstract: This work presents a machine learning framework that leverages an autoencoder (AE) for the efficient modeling of FinFET. We first calibrated a BSIM-CM

RASC+: Retrieval-Constrained LLM Adjudication for Clinical Value Set Authoring

arXiv:2606.23992v1 Announce Type: cross Abstract: Clinical value sets define the standardized terminology codes used in quality measurement, phenotyping, cohort construction, and clinical decision sup

RAVEN: A Regime-Aware Variable-context Expert Network for Financial Time Series Forecasting

arXiv:2606.24062v1 Announce Type: cross Abstract: Financial time series forecasting presents structural challenges absent from standard benchmarks. Log-returns are non-stationary, exhibit exceptionall

RE4: Transformation-aware Imitation of Object Interactions Using Manipulation Modes

arXiv:2606.24403v1 Announce Type: cross Abstract: Object interaction tasks have been a focus of advances in imitation learning. End-to-end methods, dominated by diffusion and flow-based variants have

Real-Time Interactive Music Generation via Data-Free Streaming Consistency Distillation

arXiv:2606.24307v1 Announce Type: cross Abstract: Interactive music and live performance relies on real-time human expression, but modern generative music AI remains largely absent from this domain du

REALM: A Unified Red-Teaming Benchmark for Physical-World VLMs

arXiv:2606.23892v1 Announce Type: new Abstract: Vision-language models (VLMs) are increasingly used as perception-reasoning backbones for embodied intelligence in safety-critical physical systems, whe

Reasoning as Attractor Dynamics: Latent Memory Retrieval via Gibbs-Weighted Energy Minimization

arXiv:2606.24543v1 Announce Type: new Abstract: Large Language Models (LLMs) are traditionally viewed as autoregressive generators. However, from the perspective of collective computation, they functi

REDI-Match: Rotation-Equivariant Distillation for Efficient and Robust Dense Matching

arXiv:2606.24330v1 Announce Type: new Abstract: Vision Foundation Models (VFMs) have significantly advanced dense feature matching, yet severe in-plane rotation remains a critical challenge. Existing

ReMMD: Realistic Multilingual Multi-Image Agentic Verification for Multimodal Misinformation Detection

arXiv:2606.24112v1 Announce Type: new Abstract: Multimodal misinformation detection is increasingly important because viral posts now combine long multilingual narratives, several images, mixed proven

Representation Interventions Enable Lifelong Knowledge Memory Control in LLMs

arXiv:2511.20892v4 Announce Type: replace Abstract: Large language models (LLMs) often produce incorrect or outdated content after being employed. Efficient and accurate knowledge updates without cost

RetiSEM: Generalising Causal Models for Fragmented Biomedical Data

arXiv:2606.24488v1 Announce Type: cross Abstract: Learning causal models from fragmented biomedical data is challenging because clinical, molecular, and imaging variables are often incomplete or not j

Revealing Training Data Exposure in Vision Language Large Models via Parameter Gradients

arXiv:2606.24774v1 Announce Type: new Abstract: Vision-Language Large Models (VLLMs) trained on massive crawled corpora raise pressing copyright and data-provenance concerns. These concerns are partic

Reward-Centered ReST-MCTS: A Robust Decision-Making Framework for Robotic Manipulation in High Uncertainty Environments

arXiv:2503.05226v2 Announce Type: replace-cross Abstract: Monte Carlo tree search is attractive for robotic manipulation because it can improve action selection through simulation without requiring a

Right alongside Cursor, Devin Desktop (Windsurf) and CLI now support GLM-5.2 as well. FrontierCode Extended is a benchmark we care deeply ab…

model-releaseszhipu-ai--x

Right alongside Cursor, Devin Desktop (Windsurf) and CLI now support GLM-5.2 as well. FrontierCode Extended is a benchmark we care deeply about for real-world engineering tasks, so it's great to see G

RoPE-Aware Bit Allocation for KV-Cache Quantization

arXiv:2606.24033v1 Announce Type: cross Abstract: Existing low-bit KV-cache quantizers often treat each cached key as a flat vector. Under RoPE, however, a key's contribution to a future attention log

Rule2Text: A Framework for Generating and Evaluating Natural Language Explanations of Knowledge Graph Rules

arXiv:2508.10971v2 Announce Type: replace-cross Abstract: Knowledge graphs (KGs) can be enhanced through rule mining; however, the resulting logical rules are often difficult for humans to interpret d

SAFARI: Scaling Long Horizon Agentic Fault Attribution via Active Investigation

arXiv:2606.24626v1 Announce Type: new Abstract: As autonomous agents tackle increasingly complex multi-step, multi-agent tasks, their execution trajectories have scaled beyond the constraints of even

Sakana AI CEO David Ha (@hardmaru) appeared on TBS CROSS DIG’s “1on1 Tech.” He talks about our founding story, latest research and technical…

model-releasesdavid-ha--x

Sakana AI CEO David Ha (@hardmaru) appeared on TBS CROSS DIG’s “1on1 Tech.” He talks about our founding story, latest research and technical vision, product launches including Sakana Fugu, Japan’s AI

Sample session: https://claude.ai/code/session_01JptTG6Pr3NGWxQXMM3vWvi

model-releasessimon-willison--x

This entry references a Claude.ai coding session shared by Simon Willison, a well-known technology writer and open source developer, likely demonstrating a practical example of using Claude's code int

SciZoom: A Large-scale Benchmark for Hierarchical Scientific Summarization across the LLM Era

arXiv:2603.16131v2 Announce Type: replace Abstract: The explosive growth of AI research has created unprecedented information overload, increasing the demand for scientific summarization at multiple l

SEAGAN: domain-Specific and Edge-Aware Graph Attention Network for Dynamic Plant Processes

arXiv:2606.19623v2 Announce Type: replace Abstract: Graph neural networks (GNNs) offer a flexible framework for learning from scientific data with physical, biological, or functional associations. One

Self-Recognition Finetuning can Prevent and Reverse Emergent Misalignment

arXiv:2606.23700v1 Announce Type: cross Abstract: Emergent misalignment (EM) has been linked to the activation of misaligned persona vectors and evil character traits, suggesting that EM operates thro

SER: Learning to Ground Video Reasoning with Semantic Evidence Rewards

arXiv:2606.24726v1 Announce Type: new Abstract: Video MLLMs often struggle with fine-grained spatio-temporal reasoning, sometimes generating correct answers based on irrelevant frames or objects. Alth

SICI: A Semantic-Pragmatic Complexity Index Reveals Regime Shifts in LLM Stance Detection

arXiv:2606.13189v2 Announce Type: replace Abstract: Prompt-based LLMs are increasingly used for stance detection, but harder examples are not always repaired by clearer instructions, reasoning prompts

SignNet-1M: Large-Scale Multilingual Sign Language Video Dataset with Downstream Benchmarks

arXiv:2606.24361v1 Announce Type: new Abstract: Sign language models are typically trained on datasets captured under constrained conditions, with limited viewpoint, background, and signer-identity di

simonw/browser-compat-db

model-releasessimon-willison

simonw/browser-compat-db Inspired by Mozilla's new MDN MCP service - source code here - I decided to try converting their comprehensive mdn/browser-compat-data repository full of browser compatibility

Sources: Google AI researchers Jonas Adler and Alexander Pritzel, both viewed internally as key contributors to Gemini, are planning to leave for Anthropic (Bloomberg)

Bloomberg: Sources: Google AI researchers Jonas Adler and Alexander Pritzel, both viewed internally as key contributors to Gemini, are planning to leave for Anthropic — Two leading artificial intellig

model-releasestechmeme

Sources: in a letter to US officials, Anthropic accused Alibaba of adversarial distillation, accessing Claude 28.8M times from April to June via ~25K accounts (Maggie Eastland/Bloomberg)

Maggie Eastland / Bloomberg: Sources: in a letter to US officials, Anthropic accused Alibaba of adversarial distillation, accessing Claude 28.8M times from April to June via ~25K accounts — Anthropic

model-releasestechmeme

SP-Mind: An Autonomous Reasoning Agent for Spatial Proteomics Analysis

arXiv:2606.24235v1 Announce Type: new Abstract: Spatial proteomics enables single-cell-resolution characterization of protein expression within tissue architecture, playing a critical role in understa

Structural Kolmogorov-Arnold Convolutions: Learnable Function on the Values or the Filter Shape as Parameter-Efficient Alternative to Per-Edge Convolutional KANs

arXiv:2606.24371v1 Announce Type: cross Abstract: Convolutional Kolmogorov--Arnold Networks (KANs) replace the fixed weights of a convolutional kernel with learnable univariate functions. The dominant

SURGELLM: Rethinking Multi-Task Evaluation through Task-Aware Feature Gating with Class-Balanced Normalization

arXiv:2606.24259v1 Announce Type: cross Abstract: Fine-tuned encoders deployed across heterogeneous NLP tasks face three compounding problems: mismatched inductive biases, class-imbalance corruption o

Synergizing Physically Constrained MCMC and Chemical-Informed Gaussian Processes for Reaction Network Discovery

arXiv:2606.23757v1 Announce Type: cross Abstract: Extracting interpretable governing equations from sparse, noisy chemical time-series data remains difficult because discrete reaction topology and con

Systematic Exploration of 4-Expert Heterogeneous Mixture-of-Experts via Automated Pipeline Search

arXiv:2606.23739v1 Announce Type: cross Abstract: We present an automated large-scale search pipeline for heterogeneous 4-Expert Mixture-of-Experts (MoE4) architectures within the LEMUR neural network