Search: “model-releases”

Mean Accuracy Is the Wrong Estimand for a Release Decision

arXiv:2610.16825v1 Announce Type: new Abstract: A release decision about a fine-tuned model is an operational commitment about the next rerun of its training recipe. Yet standard benchmark reporting g

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Merit: Making every modality earn its contribution in multimodal attention decoding

DGX agent

arXiv:2610.17507v1 Announce Type: new Abstract: More than 1.5 billion people have hearing loss. When several people talk at once, hearing aids amplify every voice alike. Auditory attention decoding (A

model-releasesarxiv-cs-lg

14 Oct 2026

Meta-Video: Efficient Standardized Evaluation for Video Understanding

arXiv:2610.18535v1 Announce Type: new Abstract: Video understanding benchmarks are the primary yardstick for measuring progress in video-language modeling, and a growing body of work relies on them to

MFVSR: A Multi-Style and Fine-Grained Benchmark for Video Subtitle Removal

arXiv:2610.18461v1 Announce Type: new Abstract: Video subtitle removal (VSR) is an important video restoration task, yet existing evaluation remains limited by low-resolution datasets, fragmented test

MHVF: Training-Free GUI Grounding via Verification-Guided Multi-Hypothesis Search

arXiv:2610.17792v1 Announce Type: new Abstract: GUI grounding enables web agents to translate natural-language instructions into actionable interface locations. However, dense layouts and small, visua

MiMaAlign: Hierarchical Micro-Macro Alignment for Physically Plausible Video Generation

arXiv:2610.16482v1 Announce Type: new Abstract: Text-to-video (T2V) diffusion models have made remarkable progress in generating high-fidelity visuals, yet their outputs still often exhibit physically

Minimax Optimality of Shampoo for Nonstationary Stochastic Optimization

arXiv:2610.16923v1 Announce Type: cross Abstract: We develop a comprehensive theoretical analysis of Matrix Shampoo for tracking time-varying optima in nonstationary stochastic optimization. We derive

Mixed Precision Scaling Laws for Quantized Pretraining

arXiv:2610.17637v1 Announce Type: new Abstract: Since scaling laws were introduced for modern LLMs (Kaplan et al., 2020), several works have extended them to account for quantization, tracking the eme

MLAfication: Efficiently Enabling High-Fidelity MLA for Modern LLMs

arXiv:2610.17202v1 Announce Type: new Abstract: Multi-Head Latent Attention (MLA) compresses the KV cache into a latent representation, reducing inference memory and bandwidth. Existing MHA2MLA/TransM

MMTA: Benchmarking Multimodal Temporal Analysis with Time Series, Text, and Vision

arXiv:2610.17856v1 Announce Type: new Abstract: Time-series analysis is increasingly studied in multimodal settings, yet most benchmarks pair temporal signals with text or with visualizations derived

Monarch-Muon: Structure-Aware Muon for Fast and Memory-Efficient Pretraining

arXiv:2610.17429v1 Announce Type: new Abstract: Training large language models is constrained by both wall-clock time and memory footprint, and recent matrix-aware optimizers sharpen this tradeoff: Mu

Monitoring for Shifts at Unknown Times: Parameter-Free Conditional Conformal Martingales

arXiv:2610.17343v1 Announce Type: cross Abstract: Conditional conformal test martingales provide sequential tests for detecting distribution shifts, using a fixed reference dataset to avoid contaminat

Moving a running model's layers between GPUs mid-reply (8 ms, no re-prefill)

model-releasesr-localllama

I've been working on an inference engine called jitllm. The idea came from my background in operating systems and JIT compilers: generate kernels for whatever hardware is there, and treat layers a bit

MultiAlloc: Budget-Aware Precision Allocation for KV Cache Quantization

arXiv:2610.18642v1 Announce Type: new Abstract: The Key-Value (KV) cache constitutes a dominant source of memory consumption during large language model (LLM) inference, particularly in long-context a

Multimodal Fusion of RGB and Complementary Modalities for Semantic Segmentation

arXiv:2610.17800v1 Announce Type: new Abstract: Multi-modal semantic segmentation adds an auxiliary sensing stream to RGB images (RGB-X), such as thermal, LiDAR, depth, event, polarization, or light f

muse wonder sota on hard document ocr tasks the more you know!

model-releasesjerry-liu--x

muse wonder sota on hard document ocr tasks the more you know! We benchmarked Gemini 4 Argon, Muse Wonder, and Muse Spark comprehensively on hard document OCR tasks. They're all pretty good! - Muse Sp

NBCLT: Parameter-Agnostic Norm-Ball Clipped Local Training

arXiv:2610.17913v1 Announce Type: new Abstract: Distributed learning with multiple local steps reduces communication but aggravates drift, and its practical performance often depends on carefully tune

Neural Bayesian Networks for Modular and Scalable Decision-Making Under Uncertainty

arXiv:2610.16902v1 Announce Type: cross Abstract: Bayesian Networks (BNs) are established tools for letting agents reason under uncertainty in sequential decision-making. They split a joint distributi

Neural Dimensional Analysis: Foundations of Dimensionless and Scale-Consistent Computation

arXiv:2610.17969v1 Announce Type: new Abstract: Modern Transformers rely on many scale-control mechanisms, including normalization, residual scaling, attention temperatures, loss weighting, and adapti

New impressive work from Microsoft and collaborators. And it's one of my favorite recent topics: RL environments. They show that Qwen3.6-35B…

New impressive work from Microsoft and collaborators. And it's one of my favorite recent topics: RL environments. They show that Qwen3.6-35B-A3B goes from 41.1 to 53.3 on Terminal-Bench 2.1 by trainin

model-releasesdair-ai--x

New model from Telperion: Qwen3.8-27B-MLA & Qwen3.8-27B-GLA-g2. 4x smaller KV cache, smarter, and more efficient reasoning.

model-releasesr-localllama

Hello! We've been busy at Telperion with a lot of experimental research (more coming soon). Today, we're announcing the release of our latent attention variants of Qwen3.8-27B. Our latent attention va

New open source app built with Together AI! Gloss turns your saved articles, PDFs, and X bookmarks into a beautiful personal library, with l…

model-releasestogether-ai--x

New open source app built with Together AI! Gloss turns your saved articles, PDFs, and X bookmarks into a beautiful personal library, with lightning-fast AI answers powered by DeepSeek V4.1 Flash. Try

New open source demo app built by DeepSeek V4.1 Flash on Together AI! Try it → https://usegloss.io

model-releasestogether-ai--x

New open source demo app built by DeepSeek V4.1 Flash on Together AI! Try it → https://usegloss.io Introducing Gloss! A beautiful new way to save, read, and interact with articles. → Save articles, PD

Next-Concept Modeling: Fast, Parallel Coarse-to-Fine Text Generation

arXiv:2610.14162v1 Announce Type: cross Abstract: Diffusion language models (DLMs) offer parallel sampling for faster generation than autoregressive models, an increasingly important advantage as infe

NVIDIA Nemotron Bolt 3.5 74B A9B releases Oct. 15th

model-releasesr-localllama

This model is a 74B parameter, 9B-active-parameter mixture-of-experts (MoE) model, packed into 24GB using 2-bit quantization with advanced quantization-aware training techniques to retain quality. It

Observation Quality in DSM-Assisted Aerial Localization: A Benchmark and Base-Anchored Uncertainty Calibration

arXiv:2610.18564v1 Announce Type: new Abstract: Aerial map matching provides position observations for navigation, but a position error alone does not determine how an observation should be weighted.

Observe, Share, or Predict? Disentangling Partner Information in Embodied Multi-Agent Collaboration

model-releasesarxiv-cs-ro

arXiv:2610.16895v1 Announce Type: cross Abstract: LLMs are used as high-level controllers for embodied agents, but it remains unclear whether they support collaborative reasoning, such as anticipating

Offensive security startup CodeWall launches with $4M for AI agents that attack enterprises

model-releasessiliconangle

London-based offensive security startup CodeWall Ltd. officially launched today with 4 million in new funding to give enterprises such as banks autonomous artificial intelligence agents that attack th

OmniCompass: A Holistic Benchmark for Omni-Modal Video Grounding and Understanding

arXiv:2610.18829v1 Announce Type: new Abstract: With the rapid development of multimodal large language models (MLLMs), evaluating their video understanding capabilities has become increasingly import

OmniRaindrop: A Comprehensive Benchmark for Dual-Focused Raindrop Removal under Day and Night Scenes

arXiv:2510.17719v3 Announce Type: replace Abstract: Adherent raindrops on camera lenses are a pervasive source of real-world image degradation, undermining outdoor visual perception for downstream app

On the Depth Transfer of Neural Optimizers via L-Smoothness

arXiv:2610.14344v1 Announce Type: new Abstract: Scaling deep learning models efficiently requires predictable performance transfer across compute regimes. Establishing reliable hyperparameter transfer

On the Monitorability of Natural Language Autoencoders: Identification vs Discrimination

arXiv:2610.18727v1 Announce Type: new Abstract: Natural Language Autoencoders (NLAs) are proposed as oversight tools for language models: an Activation Verbaliser (AV) writes an English explanation of

On the Statistical Mechanics of Attention

arXiv:2610.17347v1 Announce Type: new Abstract: We revisit the statistical mechanics of Transformer attention via modern Hopfield models. We present a free-energy formalism to characterize parameter r

One Size Does Not Fit All: Distribution-Guided Tensor-Wise Adaptive Sparsification for Model Merging

arXiv:2508.06163v2 Announce Type: replace-cross Abstract: Merging multiple task-specific fine-tuned checkpoints into a single multi-task model provides an attractive alternative to joint multi-task tr

One-Way Coupling via Patchwise Adaptive Normalization in Transformer Surrogates

arXiv:2610.14687v1 Announce Type: new Abstract: Many physical systems exhibit one-way coupling: exogenous fields such as medium density or obstacle geometry influence the dynamics without being affect

Online LLM Personalization from Pairwise Preferences Across Users

arXiv:2610.17203v1 Announce Type: new Abstract: Large language models can answer the same question in different styles, but users' preferred styles are hidden and vary across users and questions. We s

Open Foundation Models in Healthcare: Challenges, Paradoxes, and Opportunities with GenAI Driven Personalized Prescription

arXiv:2502.04356v2 Announce Type: replace-cross Abstract: In response to the success of proprietary Large Language Models (LLMs), there is a growing interest in developing open, non-proprietary LLMs a

Open-o3-Video-v2: Seek, Ground, and Reason with Verifiable Spatio-Temporal Evidence

arXiv:2610.17656v1 Announce Type: new Abstract: Reliable video reasoning requires models to produce correct answers and expose supporting visual evidence. Open-o3-Video enables verifiable reasoning by

OpenAI Employee Uses 'Unnamed Chatbot' to Spy on OpenAI, Gets Arrested by FBI

OpenAI is in the news again. This time, it’s due to a recent incident involving corporate espionage. According to a statement the AI lab released on 13th October, the company discovered a “sophisticat

model-releasesr-chatgpt

OpenDGO: Benchmarking Multi-Agent Organizations Across Diverse Application Domains

arXiv:2610.17143v1 Announce Type: new Abstract: Large language model (LLM)-based multi-agent systems are increasingly applied across diverse domains, yet different applications require different forms

Over-parameterization Is Neither Robust nor Fragile in Matrix Sensing: A Geometric Theory of Solution Robustness

arXiv:2610.18318v1 Announce Type: new Abstract: Over-parameterization is ubiquitous in modern machine learning, yet its effect on robustness remains poorly understood. We study this question in matrix

Overcoming Catastrophic Forgetting: Continual Learning for Radar Waveform Classification

arXiv:2610.18404v1 Announce Type: cross Abstract: Automated radar waveform recognition classifies the waveform and modulation type of a received signal. As new waveform variants appear over time, a de

PACE: Temporal-Role Tactile Conditioning for Chunk-Based Insertion Policies

model-releasesarxiv-cs-ro

arXiv:2610.16308v1 Announce Type: new Abstract: Contact-rich insertion requires robots to combine visual alignment with tactile adjustment. However, existing visuotactile chunk-based policies collapse

Parameter-Efficient Multimodal Brain Tumor Segmentation With Stage-Wise Shared Adapters

arXiv:2610.18571v1 Announce Type: new Abstract: Different MRI modalities reveal different parts of a brain tumor. Segmentation models combine information from these modalities to outline tumor regions

PATTERN Can Be Solved from Memory: Generator-Aware Baselines for Synthetic Node Classification

arXiv:2610.15020v1 Announce Type: new Abstract: PATTERN, a synthetic node-classification benchmark still used to rank graph networks, plants a random subgraph in a random host graph and asks which nod

PC7 Model: Dynamics of Expanding and Contracting Soft Robots using Piece-wise Constant 7D Deformation Based on Similarity Transformation Group

model-releasesarxiv-cs-ro

arXiv:2610.14586v1 Announce Type: new Abstract: This paper proposes a novel soft robot model named piece-wise constant 7D deformation (PC7) model that can represent expanding and contracting deformati

Personalized Physiological-Model-Based Neural Network for Glucose Forecasting in Type 1 Diabetes

arXiv:2610.15456v1 Announce Type: cross Abstract: Accurate, physiologically consistent glucose forecasts could help people with type 1 diabetes respond to impending excursions. We applied our physiolo

Pessimistic Latent Task-aware Optimization for Robust Offline Meta-Reinforcement Learning

arXiv:2610.15428v1 Announce Type: new Abstract: Context-based offline meta-reinforcement learning (COMRL) has advanced almost entirely through better task representations, which separate task identity