Search: “model-releases”

RTLC -- Research, Teach-to-Learn, Critique: A three-stage prompting paradigm inspired by the Feynman Learning Technique that lifts LLM-as-judge accuracy on JudgeBench with no fine-tuning

arXiv:2605.13695v1 Announce Type: cross Abstract: LLM-as-a-judge is now the default measurement instrument for open-ended generation, but on the public JudgeBench benchmark even strong instruction-tun

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Safe Bayesian Optimization for Uncertain Correlations Matrices in Linear Models of Co-Regionalization

arXiv:2605.13302v1 Announce Type: new Abstract: This paper extends safety guarantees for multi-task Bayesian optimization with uncertain correlation matrices from intrinsic co-reginalization models to

Scaling Laws Meet Model Architecture: Toward Inference-Efficient LLMs

arXiv:2510.18245v3 Announce Type: replace-cross Abstract: Scaling the number of parameters and the size of training data has proven to be an effective strategy for improving large language model (LLM)

scShapeBench: Discovering geometry from high dimensional scRNAseq data

arXiv:2605.12662v1 Announce Type: new Abstract: High-dimensional point cloud data arise across many scientific domains, especially single-cell biology. The shapes or topologies of these datasets deter

SCU-Hand with Integrated Single-Sheet Valve: A Funnel-Shaped Robotic Hand for Milligram-Scale Powder Handling

model-releasesarxiv-cs-ro

arXiv:2512.07091v2 Announce Type: replace Abstract: Laboratory Automation (LA) has the potential to accelerate solid-state materials discovery by enabling continuous robotic operation without human in

See you in Singapore. BTW, I'm starting to look more and more like our logo.

model-releaseszhipu-ai--x

Zhipu AI announced plans to attend an event or conference in Singapore while making a lighthearted comment about their appearance increasingly resembling their company logo. The post appears to be a c

Seg-Agent: Test-Time Multimodal Reasoning for Training-Free Language-Guided Segmentation

arXiv:2605.12953v1 Announce Type: cross Abstract: Language-guided segmentation transcends the scope limitations of traditional semantic segmentation, enabling models to segment arbitrary target region

Senses Wide Shut: A Representation-Action Gap in Omnimodal LLMs

arXiv:2605.13737v1 Announce Type: new Abstract: When an omnimodal large language model accepts a question whose textual premise contradicts what it actually sees or hears, does the failure lie in perc

SkySplat: Generalizable 3D Gaussian Splatting from Multi-Temporal Sparse Satellite Images

arXiv:2508.09479v2 Announce Type: replace Abstract: Three-dimensional scene reconstruction from sparse-view satellite images is a long-standing and challenging task. While 3D Gaussian Splatting (3DGS)

SMA: Submodular Modality Aligner For Data Efficient Multimodal Learning

arXiv:2605.12872v1 Announce Type: new Abstract: Despite the recent success of Multimodal Foundation Models (FMs), their reliance on massive paired datasets limits their applicability in low-data and r

Small Area Estimation of Case Growths for Timely COVID-19 Outbreak Detection

arXiv:2312.04110v2 Announce Type: replace-cross Abstract: The COVID-19 pandemic has exerted a profound impact on the global economy and continues to exact a significant toll on human lives. The COVID-

Sockpuppetting: Jailbreaking LLMs by Combining Prefilling with Optimization

arXiv:2601.13359v2 Announce Type: replace-cross Abstract: Prefill attacks are an effective and low-cost jailbreaking method, as they directly insert an acceptance sequence (e.g., 'Sure, here is how to

Sources: Microsoft plans to remove most of its Claude Code licenses and push its developers toward GitHub Copilot CLI, after previously pushing Claude Code (Tom Warren/The Verge)

Tom Warren / The Verge: Sources: Microsoft plans to remove most of its Claude Code licenses and push its developers toward GitHub Copilot CLI, after previously pushing Claude Code — Thousands of Micro

model-releasestechmeme

SpatialReward: Bridging the Perception Gap in Online RL for Image Editing via Explicit Spatial Reasoning

arXiv:2602.07458v4 Announce Type: replace Abstract: Online Reinforcement Learning (RL) offers a promising avenue for complex image editing but is currently constrained by the scarcity of reliable and

SpectralTrain: A Universal Framework for Hyperspectral Image Classification

arXiv:2511.16084v2 Announce Type: replace-cross Abstract: Hyperspectral image (HSI) classification typically involves large-scale data and computationally intensive training, which limits the practica

SpikeProphecy: A Large-Scale Benchmark for Autoregressive Neural Population Forecasting

arXiv:2605.12992v1 Announce Type: cross Abstract: Neural population models, which predict the joint firing of many simultaneously recorded neurons forward in time, are typically evaluated by a single

SpurAudio: A Benchmark for Studying Shortcut Learning in Few-Shot Audio Classification

arXiv:2605.13672v1 Announce Type: new Abstract: Few-shot classification (FSC) is widely used for learning from limited labeled data, yet most evaluations implicitly assume that target concepts are ind

State-Space NTK Collapse Near Bifurcations

arXiv:2605.12763v1 Announce Type: new Abstract: Rich feature learning in tasks that unfold over time often requires the model to pass through bifurcations, constituting qualitative changes in the unde

Stochastic Dimension-Free Zeroth-Order Estimator for High-Dimensional and High-Order PINNs

arXiv:2603.24002v2 Announce Type: replace Abstract: Physics-Informed Neural Networks (PINNs) for high-dimensional and high-order partial differential equations (PDEs) are primarily constrained by the

StreamGaze: Gaze-Guided Temporal Reasoning and Proactive Understanding in Streaming Videos

arXiv:2512.01707v3 Announce Type: replace-cross Abstract: Streaming video understanding requires models not only to process temporally incoming frames, but also to anticipate user intention for realis

Stress-Testing the Reasoning Competence of LLMs With Proofs Under Minimal Formalism

arXiv:2605.12524v1 Announce Type: cross Abstract: We introduce ProofGrid, a benchmark suite for evaluating LLM reasoning through machine-checkable proofs rather than final answers alone. ProofGrid con

SupChain-Bench: Benchmarking Large Language Models for Real-World Supply Chain Management

arXiv:2602.07342v2 Announce Type: replace Abstract: Large language models (LLMs) have shown promise in complex reasoning and tool-based decision making, motivating their application to real-world supp

Supports Kimi Code CLI, Claude Code, Cursor, Codex, Hermes, and more. Try it at: http://kimi.com/features/webbridge and the Chrome Web Store…

model-releaseskimi-moonshot--x

Kimi (by Moonshot) offers a web bridge feature that integrates with multiple AI coding tools and IDEs including Kimi Code CLI, Claude Code, Cursor, Codex, and Hermes. The feature is accessible through

SynCABEL: Synthetic Contextualized Augmentation for Biomedical Entity Linking

arXiv:2601.19667v2 Announce Type: replace-cross Abstract: We present SynCABEL (Synthetic Contextualized Augmentation for Biomedical Entity Linking), a framework that addresses a central bottleneck in

Systematic Failures in Collective Reasoning under Distributed Information in Multi-Agent LLMs

arXiv:2505.11556v4 Announce Type: replace-cross Abstract: Multi-agent systems built on large language models (LLMs) are expected to enhance decision-making by pooling distributed information, yet syst

Table-R1: Region-based Reinforcement Learning for Table Understanding

arXiv:2505.12415v3 Announce Type: replace-cross Abstract: Tables present unique challenges for language models due to their structured row-column interactions, necessitating specialized approaches for

The Building AI Agents with MongoDB and LangGraph Skill Badge can be yours on May 28th. Here's how you earn it 👉 Join our LIVE workshop, bu…

model-releasesharrison-chase--x

The Building AI Agents with MongoDB and LangGraph Skill Badge can be yours on May 28th. Here's how you earn it 👉 Join our LIVE workshop, build a real agent with MongoDB, Claude Sonnet, and LangGraph,

The critical slowing down in diffusion models

arXiv:2605.12597v1 Announce Type: cross Abstract: Computational sampling has been central to the sciences since the mid-20th century. While machine-learning-based approaches have recently enabled majo

The Geometry of LLM Quantization: GPTQ as Babai's Nearest Plane Algorithm

arXiv:2507.18553v4 Announce Type: replace Abstract: Quantizing the weights of large language models (LLMs) from 16-bit to lower bitwidth is the de facto approach to deploy massive transformers onto mo

the langsmith team cooked on this one @jakebroekhuizen this + claude code + langsmith cli has been 🔥

model-releasesharrison-chase--x

the langsmith team cooked on this one @jakebroekhuizen this + claude code + langsmith cli has been 🔥 🚀Launching: LangSmith Engine LangSmith Engine is an agent that sits on top of your traces It runs i

The table in HTML format for easier (and non-truncated) viewing: https://sebastianraschka.com/llm-architecture-gallery/active-parameter-rati…

model-releasessebastian-raschka--x

Sebastian Raschka shared an HTML-formatted table comparing active parameter ratios across different large language model architectures for improved readability and to avoid text truncation. The resour

The Tesla Semi could be a big deal for electric trucking

model-releasesmit-tech-review

The Tesla Semi has officially arrived. The company recently released a photo of the first vehicle rolling off its new full-scale production line. This moment has been nearly a decade in the making: Th

TiCo: Time-Controllable Spoken Dialogue Model

arXiv:2603.22267v2 Announce Type: replace-cross Abstract: We introduce TiCo, a time-controllable spoken dialogue model (SDM) that follows time-constrained instructions (e.g., 'Please generate a respon

Tighter Learning Guarantees on Digital Computers via Concentration of Measure on Finite Spaces

arXiv:2402.05576v4 Announce Type: replace Abstract: Machine learning models with inputs in a Euclidean space R^d, when implemented on digital computers, generalize, and their generalization gap conver

TokaMind for Power Grid: Cross-Domain Transfer from Fusion Plasma

arXiv:2605.11033v1 Announce Type: cross Abstract: TokaMind is a multi-modal transformer (MMT) foundation model pre-trained on tokamak plasma diagnostics data from MAST, where it was shown to outperfor

ToolWeave: Structured Synthesis of Complex Multi-Turn Tool-Calling Dialogues

arXiv:2605.12521v1 Announce Type: cross Abstract: Multi-turn tool calling is essential for LLMs to function as autonomous agents, yet synthesizing the training data required for these capabilities rem

Topo-R1: Detecting Topological Anomalies via Vision-Language Models

arXiv:2603.13054v2 Announce Type: replace Abstract: Topology is critical in tubular structures such as blood vessels, nerve fibers, and road networks, where connectivity and loop structure govern down

TouchAnything: A Dataset and Framework for Bimanual Tactile Estimation from Egocentric Video

model-releasesarxiv-cs-ro

arXiv:2605.13083v1 Announce Type: new Abstract: Egocentric human video data, which captures rich human-environment interactions and can be collected at scale, has become a key driver of embodied intel

Toward AI-Driven Digital Twins for Metropolitan Floods: A Conditional Latent Dynamics Network Surrogate of the Shallow Water Equations

arXiv:2605.13761v1 Announce Type: new Abstract: AI-driven flood digital twins demand fast hydrodynamic surrogates for ensemble forecasting and observation assimilation. Yet even GPU-accelerated two-di

Toward Scalable Verifiable Reward: Proxy State-Based Evaluation for Multi-turn Tool-Calling LLM Agents

arXiv:2602.16246v3 Announce Type: replace Abstract: Interactive large language model (LLM) agents operating via multi-turn dialogue and multi-step tool calling are increasingly used in production. Ben

Towards Long-horizon Embodied Agents with Tool-Aligned Vision-Language-Action Models

arXiv:2605.13119v1 Announce Type: cross Abstract: Vision-language-action (VLA) models are effective robot action executors, but they remain limited on long-horizon tasks due to the dual burden of exte

Training Large Language Models to Predict Clinical Events

arXiv:2605.12817v1 Announce Type: cross Abstract: Longitudinal clinical notes contain rich evidence of how patients evolve over time, but converting this signal into training supervision for clinical

Training LLMs with Reinforcement Learning for Intent-Aware Personalized Question Answering

arXiv:2605.12645v1 Announce Type: cross Abstract: Effective personalized question answering (PQA) in language models requires grounding responses in the user's underlying intent, where intent refers t

Uncertainty-Aware Prediction of Lung Tumor Growth from Sparse Longitudinal CT Data via Bayesian Physics-Informed Neural Networks

arXiv:2605.13560v1 Announce Type: new Abstract: This work studies lung tumor growth prediction from sparse and irregular longitudinal computed tomography (CT) observations with measurement variability

Uncertainty-Driven Anomaly Detection for Psychotic Relapse Using Smartwatches: Forecasting and Multi-Task Learning Fusion

arXiv:2605.13816v1 Announce Type: new Abstract: Digital phenotyping enables continuous passive monitoring of behavior and physiology, offering a promising paradigm for early detection of psychotic rel

Understanding and Accelerating the Training of Masked Diffusion Language Models

arXiv:2605.13026v1 Announce Type: cross Abstract: Masked diffusion models (MDMs) have emerged as a promising alternative to autoregressive models (ARMs) for language modeling. However, MDMs are known

Understanding Catastrophic Forgetting In LoRA via Mean-Field Attention Dynamics

arXiv:2402.15415v2 Announce Type: replace Abstract: Low-Rank Adaptation (LoRA) is the dominant parameter-efficient fine-tuning method due to its favorable compute-performance trade-off, yet it suffers

UNIV: Unified Foundation Model for Infrared and Visible Modalities

arXiv:2509.15642v3 Announce Type: replace Abstract: Joint RGB-infrared perception is essential for achieving robustness under diverse weather and illumination conditions. Although foundation models ex