Search: “model-releases”

Black-Box Continual Learning for Vision-Language Models

arXiv:2606.22999v1 Announce Type: new Abstract: The rapid deployment of Vision-Language Models (VLMs) in dynamic environments necessitates the ability to learn continuously without forgetting. However

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BranchShine: Compact Raw-Audio-to-IPA Transcription with a RoPE E-Branchformer Encoder

DGX agent

arXiv:2606.22824v1 Announce Type: new Abstract: Speech-to-IPA transcription is useful when the desired output is pronunciation rather than orthographic text, but competitive multilingual systems are o

model-releasesarxiv-cs-lg

23 Jun 2026

Bring open models to where you're already working. FireConnect brings Fireworks' top models directly into Claude Code, Pi, OpenCode, and Cod…

model-releasesfireworks-ai--x

Bring open models to where you're already working. FireConnect brings Fireworks' top models directly into Claude Code, Pi, OpenCode, and Codex. Watch our Head of AI Education @Prof_oz show you how: Ho

CAOA -- Completion-Assisted Object-CAD Alignment

arXiv:2606.18429v2 Announce Type: replace Abstract: Accurately aligning CAD models to their corresponding objects in indoor RGB-D scans is a central challenge in 3D semantic reconstruction. The task r

CapRiCorn-1K: A Comprehensive Benchmark for Video Captioning and Subject Referential Consistency Across Temporal Scales

arXiv:2606.21949v1 Announce Type: new Abstract: Accurate and comprehensive video captions with consistent subject references are critical for downstream understanding and generation tasks. However, fe

Catching Lies Without Sending the Video: Privacy-Preserving Multimodal Deception Detection

arXiv:2606.22699v1 Announce Type: new Abstract: Frontier multimodal models can guess whether a person is lying from a testimony video. To do so, they stream that raw face and voice to a third-party mo

CDER-SME: A Cross-Device Event-RGB Micro-Expression Dataset under Multi-Level Stress Induction

arXiv:2606.20715v1 Announce Type: new Abstract: Micro-expression recognition (MER) in realistic scenarios demands high temporal sensitivity and ecological validity, yet existing benchmarks are largely

CFAgentBench: A Reproducible Environment and Benchmark for Autonomous Construction-Finance Agents

arXiv:2606.22000v1 Announce Type: cross Abstract: We introduce CFAgentBench, a reproducible, self-hostable environment and benchmark for autonomous construction-finance agents: a CFO/controller-class

Chains That See, Answers That Don't: A Multi-Aspect Evaluation Recipe for Forced Chain-of-Thought on Video-MME

arXiv:2606.22862v1 Announce Type: new Abstract: Forced chain-of-thought (CoT) is widely assumed to make vision-language models more reliable on video question answering. We propose a small three-probe

Chehre: An Emoji-Prompted Video Dataset for Perceptually Diverse Facial Expression Recognition

arXiv:2606.21657v1 Announce Type: new Abstract: Facial expressions are nonverbal social signals used in human interaction, but facial expression recognition datasets often focus on static images, basi

Chem2Gen-Bench: Benchmarking Chemical-to-Genetic Translation in Perturbation Response Space

arXiv:2606.21109v1 Announce Type: new Abstract: Virtual-cell and perturbation models are increasingly used to predict cellular responses for biomedical discovery, but chemical and genetic perturbation

CheXpercept: A Benchmark for Evaluating Expert-Level Lesion Perception in Chest X-rays

arXiv:2606.21020v1 Announce Type: new Abstract: The evaluation of vision-language models (VLMs) for chest X-ray (CXR) analysis has largely been limited to disease-presence classification without visua

ChronoLock: Protecting Videos from Unauthorized Text-to-Video Personalization

arXiv:2606.21146v1 Announce Type: new Abstract: Text-to-video (T2V) diffusion models have made it increasingly easy to synthesize realistic and temporally coherent videos, while recent personalization

Claude is really proactive with Claude Tag. You don’t need to prompt it to do work, it can do work proactively based on your instructions. I…

model-releasesboris-cherny--x

Claude is really proactive with Claude Tag. You don’t need to prompt it to do work, it can do work proactively based on your instructions. It has excellent memory and access to your data, so it can be

Claude Tag is an incredible new form factor for agents, so I think it's going to take some time to figure out the best practices, but these …

Claude Tag is an incredible new form factor for agents, so I think it's going to take some time to figure out the best practices, but these are some of my favorites 🧵 Introducing Claude Tag, a new way

model-releasesthariq--x

Clipping the Price of Adaptivity at the Tail

arXiv:2606.22669v1 Announce Type: new Abstract: Adaptive stochastic convex optimization (SCO) methods face a fundamental ``price of adaptivity'' barrier: under the standard set of assumptions, they ca

Cluster-Specific Localized Drift Detection for Efficient Batch Model Adaptation under Controlled Distribution Shift

arXiv:2606.22026v1 Announce Type: new Abstract: Machine learning systems deployed in dynamic environments frequently operate under nonstationary data distributions, where controlled distribution shift

CodePercept: Code-Grounded Visual STEM Perception for MLLMs

arXiv:2603.10757v2 Announce Type: replace Abstract: When MLLMs fail at Science, Technology, Engineering, and Mathematics (STEM) visual reasoning, a fundamental question arises: is it due to perceptual

Comparative Evaluation of Machine Learning and Deep Learning Models for Wound-Rotor Synchronous Motor Performance Prediction

arXiv:2606.21230v1 Announce Type: new Abstract: Wound rotor synchronous motors have emerged as a strong alternative that eliminates dependence on REEs. However, WRSM design requires the simultaneous o

Concept-Constrained Prompt Learning for Few-Shot CLIP Adaptation

arXiv:2606.22567v1 Announce Type: new Abstract: Few-shot prompt learning is an effective strategy for adapting CLIP to downstream tasks, but class-only prompt optimization can overfit base-class super

Confidently Wrong: Severity-Aware Calibration of Prompt-Injection Detectors under Attack Shift

arXiv:2606.22659v1 Announce Type: cross Abstract: Prompt-injection detectors are deployed as guards: a model scores an input and a downstream system trusts or blocks it on that score. I study the conf

ConnectomeBench2: A Unified Benchmark for Automated Connectomic Proofreading

arXiv:2606.21116v1 Announce Type: new Abstract: Proofreading--correcting segmentation errors in 3D brain reconstructions--is the rate-limiting step in synapse-resolution connectomics. We release Conne

CoRDE: Concept-Prior Routed Diffusion Experts for Structural Generalization in Robot Manipulation

model-releasesarxiv-cs-ro

arXiv:2606.21935v1 Announce Type: new Abstract: Diffusion models excel at capturing multi-modal action distributions in robot imitation learning. However, in multi-task and long-horizon scenarios, mon

CoSA: Correlation-Guided Change Attention with Learnable Residual Gating for Remote Sensing Change Detection

arXiv:2606.21932v1 Announce Type: new Abstract: Remote sensing change detection (CD) from bi-temporal imagery is critical for applications such as urban monitoring, disaster assessment, and environmen

CourseBlueprint: A Structured Pipeline for Adaptive Pedagogical Video Generation Grounded in Course Corpora

arXiv:2606.20608v1 Announce Type: cross Abstract: Generative text-to-video systems can produce visually fluent educational clips, but they rarely encode the pedagogical content knowledge (PCK) needed

CRAX: Fast Safe Reinforcement Learning Benchmarking

arXiv:2606.20376v2 Announce Type: replace Abstract: Safety is a core concern for deploying reinforcement learning (RL) agents in real-world domains such as robotics and autonomous driving. While bench

Curriculum Reinforcement Learning Can Incentivize Reasoning Capacity in LLMs Beyond the Base Model

arXiv:2606.22317v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) is widely viewed as a promising path toward continuously improving large language models. Recent w

Curvature-aware 3D length estimation of greenhouse cucumbers using RGB-D imaging and cubic spline arc-length integration

arXiv:2606.22439v1 Announce Type: new Abstract: Commercial greenhouse cucumber production is graded by fruit length, which drives harvest scheduling, labour allocation, and logistics. Manual measureme

CVSBench: A Comprehensive Benchmark for Cross-view Spatial Reasoning and Dreaming

arXiv:2606.22476v1 Announce Type: new Abstract: Humans can effortlessly reason about scenes across different viewpoints, yet it remains unclear whether Vision-Language Models (VLMs) possess similar cr

Data Pruning: Redundant, Problematic, and Interdependent Samples

arXiv:2606.21916v1 Announce Type: new Abstract: The performance of deep learning models is affected by not only data quantity but also data quality. Data pruning is a process by which practitioners ca

DataClaw0: Agentic Tailoring Multimodal Data from Raw Streams

arXiv:2606.21337v1 Announce Type: new Abstract: Massive unstructured multimodal streams suffer from high 'data entropy,' impeding both efficient human knowledge acquisition and high-quality AI post-tr

Decoupling the Declarative from the Procedural in Vision-Language-Action Models

arXiv:2606.21496v1 Announce Type: cross Abstract: Deploying generalist robotic agents in the real world requires transferable skills. Specifically, a policy trained to clone a behavior from object-spe

Deep Learning-Based Sign Language Recognition from Videos and Cross-Lingual Translation to Indian Vernaculars

arXiv:2606.22494v1 Announce Type: cross Abstract: Sign language is a primary mode of communication for the global deaf and hard-of-hearing community, yet automated tools that recognize sign gestures f

Demystifying Numerical Instability in LLM Inference: Achieving Reproducible Inference for Mission-Critical Tasks with HEAL

arXiv:2606.21023v1 Announce Type: new Abstract: As Large Language Models (LLMs) deploy into mission-critical domains (e.g., finance, medicine, and law), output reproducibility has become a strict syst

Deploy from Claude Design to Vercel

model-releasesvercel-blog

This Vercel changelog entry describes integration between Claude Design and Vercel that enables direct deployment of designs to the Vercel platform. The feature likely streamlines the workflow for dev

Detail++: Training-Free Detail Enhancer for T2I Diffusion Models

arXiv:2507.17853v3 Announce Type: replace Abstract: Recent advances in text-to-image (T2I) generation have led to impressive visual results. However, these models still face significant challenges whe

Disentangling Intrinsic Importance from Emergent Structure in Multi-Expert Orchestration

arXiv:2602.04291v2 Announce Type: replace Abstract: Multi-expert systems, where multiple Large Language Models (LLMs) collaborate to solve complex tasks, are increasingly adopted for high-performance

Distilling Collaborative Dynamics into Latent Space for Implicit Coordination in Decentralized Multi-Agent Manipulation

model-releasesarxiv-cs-ro

arXiv:2606.22982v1 Announce Type: new Abstract: Multi-arm manipulation demands precise spatiotemporal coordination, yet many centralized approaches scale poorly as team size increases. To address this

Distinguishing indistinguishable attractors: Unsupervised anomaly detection with reservoir computers

arXiv:2606.21322v1 Announce Type: new Abstract: Detecting when a nonlinear dynamical system departs from its normal regime is a recurring problem across the sciences, from cardiology to climate and en

Distributed Model Predictive Control with Adaptive Safety Zones for Multi-Fleet Drone Operations

model-releasesarxiv-cs-ro

arXiv:2606.20651v1 Announce Type: cross Abstract: Autonomous drone swarms in space-constrained environments such as warehouses, inspection corridors, and urban delivery routes must share limited airsp

Distribution-Aware Robust Bilevel Optimization: Quantile-Guided Huber Updates in Two-Timescale Stochastic Approximation

arXiv:2606.22436v1 Announce Type: new Abstract: Bilevel optimization (BLO) is fundamental to hierarchical decision-making but suffers from critical instability under heavy-tailed stochastic noise. Exi

Do Location Encoders Capture Spatial Effects? A GeoShapley Benchmark Across Scales

arXiv:2606.23453v1 Announce Type: new Abstract: Location encoders transform geographic coordinates into high dimensional embeddings for downstream machine learning, but it is unclear how well these re

Do Modern Video-LLMs Need to Listen? A Benchmark Audit and Scalable Remedy

arXiv:2509.17901v4 Announce Type: replace Abstract: Speech and audio encoders developed over years of community effort are routinely excluded from video understanding pipelines, not because they fail,

Does RoPE Prevent or Degrade Retrieval Heads? A Mechanistic Analysis Across Model Families

arXiv:2606.21249v1 Announce Type: new Abstract: Retrieval heads, attention heads that copy information from earlier context to the current position, have been proposed as the mechanistic substrate for

Double-Diffusion: Balancing Speed, Accuracy, and Uncertainty in Probabilistic Forecasting for Urban Sensor Networks

arXiv:2506.23053v3 Announce Type: replace Abstract: Urban sensor networks need forecasts that are accurate, carry useful uncertainty, and refresh fast enough to act on as new readings arrive. These go

DR-Mamba: Automatic Inference-Time Domain Adaptation for Document Image Binarization via Sample-Conditioned Detail-Background Suppression

arXiv:2606.22625v1 Announce Type: new Abstract: Degraded document image binarization is sensitive to domain shifts caused by paper aging, bleed-through, stains, shadows, and uneven illumination, and t

DrivingVoxels: Compositional Sparse Voxel Rasterization for Dynamic Driving Scene Reconstruction

arXiv:2606.23031v1 Announce Type: new Abstract: Reconstructing dynamic urban scenes remains challenging due to the unbounded nature of driving environments and the presence of multiple dynamic objects

DrugBench: Evaluating AI Control Protocols for Medication Harm Mitigation

arXiv:2606.20663v1 Announce Type: cross Abstract: Large Language Models have the potential to expand and improve the access to clinical information by enabling new ways of interacting with medical kno