Search: “model-releases”

Explain Less, Understand More: Data-Efficient Personalization of Reader-Dependent Jargons

arXiv:2505.16227v4 Announce Type: replace Abstract: Personalizing jargon detection and explanation is essential for making technical documents accessible to readers with diverse disciplinary backgroun

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Model Releases

Explainable Neuro-Fuzzy Prediction for Trustworthy Decision-Making in Maritime

DGX agent

arXiv:2609.24358v1 Announce Type: new Abstract: Predicting when maritime systems require maintenance can be critical, avoiding hazards and costly consequences. To address this problem, this paper prop

model-releasesarxiv-cs-lg

22 Sept 2026

Fairness Beyond Anonymization? Demographic Leakage in German LLM-Generated Resumes

arXiv:2609.22188v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly integrated into AI-assisted hiring pipelines, including automated resume generation and screening. Under t

Fathom-Vaidya: Advancing Medical Reasoning with Rubric-Based Rewards

arXiv:2609.24480v1 Announce Type: cross Abstract: Deploying Large Language Models (LLMs) in healthcare requires robust performance across two complementary dimensions - diagnostic reasoning: the conve

FeasibleFlow: One-Step Joint Transport of Configuration Feasibility and Trajectories for End-to-End Driving

arXiv:2609.23488v1 Announce Type: new Abstract: End-to-end autonomous driving maps current observations directly to future trajectories, yet those trajectories must remain valid as the scene evolves.

Federated Multilingual Speech-LLMs: Architecture and Aggregation Strategy Benchmarking

arXiv:2609.23825v1 Announce Type: new Abstract: We present a comprehensive benchmark of Federated Learning (FL) for multilingual Automatic Speech Recognition (ASR), evaluating four Speech-LLM architec

FlockDiffusion: Assignment-Conditioned Diffusion for Multi-Drone Task Allocation and Completion

arXiv:2609.23745v1 Announce Type: new Abstract: Autonomous multi-drone navigation requires fleets to service distributed objectives in cluttered environments under tight computational budgets. Efficie

Fork of FreeToken with DeepSeek-V4.1, vision and speculative decoding (2x3090 numbers inside)

model-releasesr-localllama

I've been running FreeToken on my 2x3090 box for a while and ended up maintaining a fork of it. Posting it in case it's useful to anyone else here. Quick context if you haven't used it: FreeToken is a

Fractal basin geometry and the limits to predictability and reproducibility in deep learning

arXiv:2510.05606v2 Announce Type: replace Abstract: Fundamental limits to predictability are central to our understanding of many physical and computational systems. In deep learning, training outcome

From Documented Strengths to Force Limits: Material-Informed Robotic Insertion for Construction Assembly

arXiv:2609.22609v1 Announce Type: new Abstract: Insertion is a fundamental operation in robotic construction assembly, where variations in material properties and assembly conditions make it difficult

From UNDRR Reports to Event Records: Schema-Constrained LLM Extraction of Georeferenced Disasters

arXiv:2609.23853v1 Announce Type: new Abstract: Disaster-risk-reduction archives describe hazard events in prose that databases such as EM-DAT (Delforge et al., 2025) cannot ingest directly. We presen

G-NAC: Graph Neural Automata Clustering via Emergent Domain Formation

arXiv:2609.24823v1 Announce Type: new Abstract: We introduce Graph Neural Automata Clustering (G-NAC), an unsupervised clustering method in which observations interact as cells on a fixed neighborhood

GameHorizon Suite: Multi-Horizon Data and Evaluation in Gameplay

arXiv:2609.25001v1 Announce Type: new Abstract: Modern video games provide a measurable testbed for AI models, combining abilities of visual understanding, instruction decomposition, goal planning, an

GameReplica: A Benchmark for Black-Box Visual Game Replication by Vision-Language Agents

arXiv:2609.22308v1 Announce Type: new Abstract: Coding-agent benchmarks usually evaluate implementation after the target behavior has been specified in text, code, or demonstrations. Existing research

Garbage Attention in Large Language Models: BOS Sink Heads and Sink-aware Pruning

arXiv:2601.06787v2 Announce Type: replace Abstract: Large Language Models (LLMs) are known to contain significant redundancy, yet a systematic explanation for why certain components, particularly in h

General Collaborative Intelligence: Architecting Cognition for Resilient Multi-Agent Ecosystems

arXiv:2609.22967v1 Announce Type: new Abstract: Multi-agent unmanned systems are moving from isolated, ego-centric sensing toward collaborative intelligence, in which distributed agents exchange compa

Generalizable Optimal Control with Transformers: One Policy Across Diverse Systems

arXiv:2603.14910v2 Announce Type: replace-cross Abstract: Classical optimal control designs a separate controller for each plant. Even for the Linear Quadratic Regulator (LQR), every new model must be

Generating Chest X-Ray Counterfactuals by Specialising Foundation Image Models

arXiv:2609.24879v1 Announce Type: new Abstract: Counterfactual image generation answers questions about how a subject would have looked under retrospective, hypothetical scenarios. Recent methods have

Glass-Box Deep Learning for FDIA Detection in Nonlinear Automatic Generation Control: A Kolmogorov-Arnold Network Approach

arXiv:2509.05259v2 Announce Type: replace Abstract: Automatic Generation Control (AGC) plays a critical role in maintaining power balance across multi-area power systems. However, its complete relianc

Global Ranks Survive, Selected Heads Shift: BOS-Sink Topology under 4-bit Weight-Only Quantization

arXiv:2609.23585v1 Announce Type: cross Abstract: Sink-aware deployment may identify important first-token attention heads before a model is quantized, then reuse that map at the edge. We test when th

GPT-6 Sol costs 2/1M input and 10/1M output tokens, and GPT-6 Luna costs 0.10/1M input and 0.50/1M output tokens, both about 50% cheaper than GPT-5.6 (Nat Rubio-Licht/The Deep View)

Nat Rubio-Licht / The Deep View: GPT-6 Sol costs 2/1M input and 10/1M output tokens, and GPT-6 Luna costs 0.10/1M input and 0.50/1M output tokens, both about 50% cheaper than GPT-5.6 — OpenAI is relea

model-releasestechmeme

GPT‑6 Sol and Luna build on Astra’s advances in alignment, showing improvements over their GPT-5.6 counterparts.

OpenAI announced the GPT‑6 Sol and Luna models on September 22 2026. These variants incorporate advances from the Astra project, yielding improved alignment safety relative to earlier GPT‑5.6 systems.

model-releasesopenai--x

Graded-Relevance Composed Multimodal Retrieval for E-commerce Visual Search at Scale

arXiv:2609.24152v1 Announce Type: cross Abstract: Visual search on large e-commerce catalogs must serve both 'similarity' queries that ask for items resembling an uploaded image and 'modifier' queries

Great prompt from Anthropic. It helps steer long runs when using Opus 5.5 in Claude Code. Apparently, on long-running tasks, the model somet…

Great prompt from Anthropic. It helps steer long runs when using Opus 5.5 in Claude Code. Apparently, on long-running tasks, the model sometimes stops to report instead of continuing. I've noticed tha

model-releasesdair-ai--x

Ground-Truth Subgraphs for Better Training and Evaluation of Knowledge Graph Augmented LLMs

arXiv:2511.04473v3 Announce Type: replace-cross Abstract: Retrieval of information from graph-structured knowledge bases represents a promising direction for improving the factuality of LLMs. While va

H2LooP Telecom Model v1: From Telecom Comprehension to Autonomous Issue and PR Resolution

arXiv:2609.22241v1 Announce Type: new Abstract: We present H2LooP Telecom Model v1, a domain-specialized large language models fine-tuned for the telecommunications industry. We release two domain-ada

H2RBench: A Real-to-Sim Benchmark for Evaluating Human-to-Robot Transfer

arXiv:2609.24778v1 Announce Type: new Abstract: Learning robot manipulation policies from human video demonstrations constitutes a promising avenue for scalable robot learning. However, comparing diff

HappyWorld-Bench

arXiv:2609.24308v1 Announce Type: new Abstract: Evaluating world models requires assessing both the quality of the worlds they generate and their consistency and responsiveness under exploration, inte

HDND: Hierarchical Dynamic Neural Decoding for Multilingual Word/Character Retrieval from Non-Invasive Brain Recordings

arXiv:2609.24095v1 Announce Type: new Abstract: While deep learning has enabled language decoding from intracranial brain recordings, extending this capability to non-invasive recordings remains an un

Hello, new to CLI and Opensource AI but running into a issue with gemma4:26b

I keep trying to get it to write code and test simpel stuff but it never finsihes conversation its always stopping mid way. i installed it through qwen > ollama. currently removed it and trying to rei

model-releasesr-ollama

HFEMCNet: A Compact Hybrid Frequency Enriched Multi Channel Network for Automatic Modulation Classification

arXiv:2609.22139v1 Announce Type: cross Abstract: Automatic modulation classification (AMC) of received radio signals is prudent for further signal processing tasks such as communication monitoring, c

Hi Ollama People!

Hi everyone, I wanted to ask you a question. I’m developing an app, and I’m currently putting together a list of the best AI models, especially, but not necessarily, in GGUF format and using Q4_K_M qu

model-releasesr-ollama

Hi-Singers: A Comprehensive High-Quality Dataset for Expressive Audio-Driven Singing Head Synthesis

arXiv:2609.22264v1 Announce Type: cross Abstract: State-of-the-art models for audio-driven digital human generation have achieved photo-realistic results in talking-head synthesis. However, extending

Hierarchical Prompt Learning for Hyperbolic Vision-Language Models

arXiv:2609.24276v1 Announce Type: new Abstract: Hyperbolic vision-language models (VLMs) represent image and text features in a geometry naturally suited to hierarchy, but their adaptation to downstre

High-resolution Nitrogen Dioxide Maps Reveal Exposure Limit Breaches across Europe

arXiv:2609.24634v1 Announce Type: new Abstract: Nitrogen dioxide (NO2) is a common air pollutant, released into the atmosphere through the incomplete burning of fossil fuels, and associated with respi

Higher usage limits and lower cost give you more flexibility and room to iterate.

In a tweet posted on September 22, 2026, OpenAI noted that increasing usage limits while lowering costs gives users greater flexibility and more room to iterate on their projects. This announcement hi

model-releasesopenai--x

Highly-Efficient Differentiable Simulation for Robotics

arXiv:2409.07107v3 Announce Type: replace Abstract: Robotics simulators have improved significantly in computational speed and scalability, enabling them to generate years of simulated data for comple

HOIBlender: Blending Lightweight Detection with Vision-Language Priors for Efficient Human-Object Interaction Detection

arXiv:2609.23431v1 Announce Type: new Abstract: Human-object interaction (HOI) detection requires grounding an interacting human-object pair and recognizing the verb that links them, often under sever

Holographic generative flows with AdS/CFT

arXiv:2601.22033v2 Announce Type: replace Abstract: Holography, in the form of the anti-de Sitter/conformal field theory (AdS/CFT) correspondence, offers a natural setting for generative modelling. Da

Human-Level Accuracy, Non-Human Strategies: Revealing Model-Human Divergence in Video Physical Reasoning

arXiv:2609.22788v1 Announce Type: new Abstract: Video foundation models now reach human-level accuracy on physical-reasoning benchmarks, yet such tasks require predicting unobserved physical outcomes.

HybridFlow: A 2-NFE Generative Policy for Real-Time Robotic Manipulation

arXiv:2602.13718v2 Announce Type: replace Abstract: Generative policies for robotic manipulation must balance action accuracy with inference latency. We present HybridFlow, a three-stage policy infere

HyperCLIP++: Fine-tuning CLIP forOpen-vocabulary Semantic Segmentation in Hyperbolic Space

arXiv:2609.24564v1 Announce Type: new Abstract: CLIP, a foundational vision-language model, has emerged as a powerful tool for open-vocabulary semantic segmentation. While freezing CLIP's text encoder

I asked 4 LLMs to invent words for things only an LLM could understand. Got a dictionary of their own bad habits instead.

You know the thing where you ask a chatbot what's wrong with your plan and it goes 'there are three problems here' and problem three is clearly the runt of the litter? There's a word for that now. An

model-releasesr-chatgpt

I used Opus 5.5 to formally verify the Claude Agent SDK using Lean. A couple short prompts = 16 PRs fixing various bugs and race conditions.…

model-releasesboris-cherny--x

I used Opus 5.5 to formally verify the Claude Agent SDK using Lean. A couple short prompts = 16 PRs fixing various bugs and race conditions. Video attached. TLA+ also works well. I sometimes combine L

Identifying Representational Biases in Datasets Using PCA: A Max-Disparity Partition Framework

arXiv:2609.24556v1 Announce Type: cross Abstract: Principal Component Analysis (PCA) minimises aggregate reconstruction error, which can inadvertently represent majority subgroups with substantially h

IMPLICIT-Bench: Measuring Implicit Bias in Text-to-Image Models under Neutral Prompts

arXiv:2609.24228v1 Announce Type: new Abstract: Text-to-image (T2I) models are typically evaluated for bias using slot-based templates such as ``a photo of a [profession]''. Such templates probe only

Impressive paper showing how much the harness changes a coding agent's results. Harnesses do play a huge role in what you are getting out of…

Impressive paper showing how much the harness changes a coding agent's results. Harnesses do play a huge role in what you are getting out of the models. GPT-5.5 was run inside both Claude Code and Cod

model-releasesdair-ai--x

Improved Private Sparse Covariance Estimation with Multiscale Threshold Tests

arXiv:2609.22783v1 Announce Type: new Abstract: We study differentially private covariance estimation in operator norm for mean-zero sub-Gaussian distributions with unknown covariance support and at m