Search: “model-releases”

ExtrinSplat: Decoupling Geometry and Semantics for Open-Vocabulary Understanding in 3D Gaussian Splatting

arXiv:2509.22225v3 Announce Type: replace-cross Abstract: Lifting 2D open-vocabulary understanding into 3D Gaussian Splatting (3DGS) scenes is a critical challenge. Mainstream methods, built on an emb

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Model Releases

Fairness-Aware Low-Rank Representation Fine-Tuning

DGX agent

arXiv:2503.05684v2 Announce Type: replace-cross Abstract: Pre-trained foundation models can be efficiently adapted for specific tasks using Low-Rank Adaptation (LoRA), but the fairness properties of t

model-releasesarxiv-cs-cv

25 Aug 2026

Federated Continual Learning as a Distributed Drift-Plus-Penalty Control Problem

arXiv:2608.21539v1 Announce Type: new Abstract: Federated Continual Learning (FCL) is fundamental to real-world distributed learning systems, requiring models to adapt to sequential, non-IID data acro

FedRP: A Communication-Efficient Approach for Differentially Private Federated Learning Using Random Projection

arXiv:2509.10041v2 Announce Type: replace Abstract: Federated learning (FL) enables collaborative model training without centralizing data, but exchanging high-dimensional updates can expose sensitive

Fidelity-Diversity-Consistency (FDC): Data Pruning for Remote Sensing Change Detection

arXiv:2608.21754v1 Announce Type: new Abstract: Despite the success of data pruning (DP) in reducing training data sizes and improving downstream model performance in classification and segmentation t

FigmaTrace: Capturing Creative Nuances in Human Figma Design Workflows

arXiv:2608.21460v1 Announce Type: cross Abstract: Vision Language Models have recently shown improvements in several objective and verifiable domains such as object detection but continue to underperf

FinixDoc: Rethinking Financial Document Parsing Beyond Saturated Benchmarks

arXiv:2608.22842v1 Announce Type: new Abstract: Financial document parsing requires accuracy, structural consistency, and verifiability that current benchmarks often fail to reflect. We present FinixD

FIXED 7900 xtx + headless Linux crashes (Low RAM OOM) amdgpu.runpm=0

model-releasesr-localllama

TL:DR: power management was doing auto-suspend and dumping model weights into RAM. Models weights 18gb+ RAM 16gb = no Bueno immediate crash. amdgpu.runpm=0 in your grub disables runtime power manageme

Frame-Level Evaluation in Weakly Supervised Video Anomaly Detection Mostly Measures Video-Level Ranking

arXiv:2608.21854v1 Announce Type: new Abstract: Weakly supervised video anomaly detectors are trained with video-level labels but are commonly evaluated as temporal localizers using Micro-AUROC or AP

From Inertia to Objectivity: Improving Deep Research Agents with Noise Isolation

arXiv:2608.23045v1 Announce Type: new Abstract: Web search agents powered by Large Language Models (LLMs) show strong promise, but deep research tasks expose a recurring failure mode: once an agent ha

From Isolation to Alignment: Unified LoRA for Efficient Multi-Task Learning

arXiv:2508.05078v2 Announce Type: replace-cross Abstract: Parameter-Efficient Fine-Tuning (PEFT) is essential for adapting Large Language Models (LLMs) to multi-task scenarios. A prevailing trend in t

From Mastery Profile to Simulated Response: Stochastic Student Knowledge Graphs (SSKG) for Faithful LLM Student Simulation

arXiv:2608.21668v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used to simulate students at different mastery levels. These simulations can generate synthetic training d

From SQL Generation to Tool Selection: A Domain-Oriented Pattern for MCP Servers

arXiv:2608.22063v1 Announce Type: new Abstract: Agents built on Large Language Models (LLMs) increasingly reach enterprise data through the Model Context Protocol (MCP), and many MCP database servers

From Subjective Judgments to Auditable Standards:Protocol-Guided AI Auditing of Website Redundancy

arXiv:2608.21476v1 Announce Type: cross Abstract: Website redundancy does not have a single fixed meaning. The same repeated element may distract during one task and provide backup during another. We

GameXpert-Bench: How Far Are Coding Agents from Expert Game Development?

arXiv:2608.21833v1 Announce Type: new Abstract: Recent large language models (LLMs) can operate as coding agents that build complete games from natural language requests. Game development is especiall

GAN-Diff : Coupling Pretrained WGAN-GP Features with Conditional Diffusion U-Nets

arXiv:2608.22272v1 Announce Type: cross Abstract: Generative adversarial networks (GANs) can provide efficient image generation, while diffusion models offer high-quality image restoration but require

Gated Decoupled Compositional Bandits: A Unified Theory of Contextual Bandits with Supervised-Calibrated Action Scaling and Pre-Execution Gating

arXiv:2608.21993v1 Announce Type: new Abstract: We introduce Gated Decoupled Compositional Bandits (GDCB), a family of contextual bandit algorithms with three structural innovations that jointly fall

Gauss--Hermite Quadrature for Gaussian-Mixture Entropy with an Action-Space Hermite Surrogate

arXiv:2608.21467v1 Announce Type: cross Abstract: Gaussian distributions are used to model uncertainty in signals and states, and Gaussian mixtures are often used when the underlying distribution is m

Gaussian process learning with flow map refinement for parameter estimation in dynamical systems

arXiv:2608.22324v1 Announce Type: new Abstract: Parameter estimation is a central task in data-driven learning of dynamical systems. It aims to recover the underlying physical parameters from observed

Google launches Gemini Enterprise for Legal, expanding its platform with specialized AI agents and integrations with Thomson Reuters, LexisNexis, and Harvey (Mike Scarcella/Reuters)

Mike Scarcella / Reuters: Google launches Gemini Enterprise for Legal, expanding its platform with specialized AI agents and integrations with Thomson Reuters, LexisNexis, and Harvey — Alphabet's Goog

model-releasestechmeme

GRACE: Step-Level Benchmark for Faithful Reasoning over Context

arXiv:2606.16151v2 Announce Type: replace Abstract: Many reasoning tasks require models to reason over input context, from document-grounded question answering to rule-based deduction. Chain-of-Though

Grounded Normative Rule Generation with Structured Search

arXiv:2608.22229v1 Announce Type: new Abstract: Normative rules like institutional charters and workplace policies must be both human-readable and operationally verifiable against actual environment r

GSAR: Goal-State-Anchor Rewards for Mobile GUI Agents with Self-Evolving Data Synthesis

arXiv:2608.22847v1 Announce Type: new Abstract: Vision-Language Models (VLMs) based GUI agents stand to benefit significantly from online reinforcement learning (RL). However, their training is bottle

GuardianBench: A Same-Scene Instruction-Contrastive Benchmark for Latent Contextual Risk in Embodied AI

arXiv:2608.21928v1 Announce Type: new Abstract: In embodied AI, safety risk can be latent: a benign instruction and a safe scene become hazardous only when composed. Prior work has advanced embodied s

GUI-Primitives: Diagnosing Spatial Reasoning Failures in Vision-Language GUI Grounding

arXiv:2608.21832v1 Announce Type: new Abstract: Computer-use agents ground natural-language instructions in screenshots to locate interface elements, yet existing benchmarks do not isolate whether mod

Guidance for Prior Change via Density Ratio Estimation

arXiv:2608.21729v1 Announce Type: cross Abstract: Simulation-Based Inference (SBI) serves as a vital framework for parameter inference in scientific fields where simulators involve intractable likelih

Guided Riemannian Optimization (GuRO): Bridging Model Predictive Control and Decision Transformers

model-releasesarxiv-cs-ro

arXiv:2608.23204v1 Announce Type: new Abstract: Decision-making in high-dimensional, nonlinear systems remains a central challenge in robotics. While model-based methods like Model Predictive Control

Hack-Verifiable Terminal Bench: Evaluating Reward Hacking in Terminal Tasks

arXiv:2608.22103v1 Announce Type: new Abstract: As agents grow more capable and autonomous, their tendency to reward hack, satisfying a task's checks while violating its intent, becomes an increasingl

Hate Speech Classification In Roman Urdu: A Comparative Study On Parameter Efficient Fine-Tuning And Prompt Engineering

arXiv:2608.21408v1 Announce Type: new Abstract: Due to the widespread accessibility of the internet and social media, toxic and hateful con-tent has grown exponentially, causing significant distress a

HAWKEYE: Seeing One Layer Deeper -- A Cohesion-Aware Structural Channel for Temporal Link Prediction

arXiv:2608.22727v1 Announce Type: cross Abstract: State-of-the-art temporal-link-prediction (TLP) models are, in essence, multi-channel information aggregators: they combine an interaction-history cha

HERO: Human-profile Enhanced Retrieval Optimization Framework for Long-term Agent Memory

arXiv:2608.22310v1 Announce Type: new Abstract: Long-term memory is crucial for personalized responses and long-horizon agent interactions. Existing methods often rely on LLMs to compress or rewrite d

Hierarchical Book Organization for Learning-Resource Discovery using Dual-Path Graph Convolutions

arXiv:2512.21076v2 Announce Type: replace-cross Abstract: The growing availability of books and textual materials in digital learning environments necessitates reliable semantic organization to suppor

Hierarchical Exponential-Gaussian Mixtures for Watch-Time Distribution Prediction

arXiv:2608.23356v1 Announce Type: cross Abstract: Accurate watch-time (WT) prediction is an important requirement for short-video recommendations. Yet WT distributions are near-zero-inflated, long-tai

Hierarchy-Aware Semantic Losses for Knowledge Graph Link Prediction

arXiv:2608.22981v1 Announce Type: new Abstract: Knowledge graphs are often accompanied by ontological class hierarchies that encode valuable semantic information, yet many link prediction methods eith

HIRA: A Human-in-the-Loop Retrieval-Augmented Cascade for Document Classification in Regulated Industries

arXiv:2608.21792v1 Announce Type: new Abstract: Document classification in regulated industries is constrained by data residency, limited cold-start labels, scarce review capacity, and costly model-go

HOT-POT: Optimal Transport for Sparse Stereo Matching

arXiv:2601.12423v2 Announce Type: replace Abstract: Stereo vision between images faces a range of challenges, including occlusions, motion, and camera distortions, across applications in autonomous dr

How do you go from jailbreaking your PlayStation to CEO of Canada's leading LLM provider? You go to the University of Toronto. 'When you go …

Cohere’s tweet discusses how someone moved from jailbreaking a PlayStation to becoming CEO of Canada’s leading LLM provider, attributing this career shift to education at the University of Toronto and

model-releasescohere--x

How Does Research Evolve? Tracing Cross-Domain Trajectories in NLP, ML, and CV Through Claim-Grounded Typed Citations

arXiv:2606.22342v2 Announce Type: replace Abstract: How does research evolve, and can we trace it at the level of individual claims? Scientific progress is not simply a uniform accumulation of facts.

How Merge-Tolerant Are Vision Transformers for Wheat Phenotyping?

arXiv:2608.23142v1 Announce Type: new Abstract: Vision-based wheat phenotyping requires repeated measurements under deployment constraints, from growth-stage recognition to wheat-head counting and org

How Much Regularization Survives Averaging? Update Masking in Federated Learning

arXiv:2608.23286v1 Announce Type: cross Abstract: Federated learning on non-IID data seeks flat minima to generalize across clients, and existing methods borrow sharpness-aware minimization from centr

How Useful are LLMs for Grammar Engineering? Cantonese ParGram Resources and Controlled Experimental Evaluation with English Baselines

arXiv:2608.23448v1 Announce Type: new Abstract: This paper presents new Cantonese ParGram resources and evaluates LLMs for knowledge-driven grammar engineering within a controlled experimental paradig

IBM Granite 4.2 is now available on Ollama. 3B, 8B, 30B parameter open models made for enterprise agents. This model is free to use and is l…

IBM Granite 4.2 is now available on Ollama. 3B, 8B, 30B parameter open models made for enterprise agents. This model is free to use and is licensed for both research and commercial usage. The data cur

model-releasesollama--x

ibm-granite/granite-4.2-30b · Hugging Face

model-releasesr-localllama

Granite-4.2-30B is the flagship reasoning model in the Granite 4.2 family. It delivers the strongest performance across reasoning-intensive tasks by leveraging built-in <think>...</think> chain-of-tho

If you keep safety rules or coding standards in an AGENTS.md or a CLAUDE.md, this one is worth your time. (bookmark it) Researchers measured…

If you keep safety rules or coding standards in an AGENTS.md or a CLAUDE.md, this one is worth your time. (bookmark it) Researchers measured what context compaction actually destroys across 20 product

model-releasesdair-ai--x

i’m seeing SO many US companies shift away from frontier models to open source in the last 4 weeks. cost and privacy are big factors but mor…

model-releasesclem-delangue--x

i’m seeing SO many US companies shift away from frontier models to open source in the last 4 weeks. cost and privacy are big factors but more so people are realising fine-tuning and training their own

Improving O-RADS Risk Stratification from Ultrasound Reports: A Comparative Evaluation of Hybrid versus End-to-End LLM Reasoning Strategies

arXiv:2608.23061v1 Announce Type: new Abstract: Background: Automating clinical guideline-based decision-making with large language models (LLMs) remains challenging because of reliability, hallucinat

Incumbent Advantage: Brand Bias and Cognitive Manipulation Dynamics in LLM Recommendation Systems

arXiv:2606.17443v2 Announce Type: replace Abstract: Large language models (LLMs) are becoming a major way for consumers to find products, but we do not yet understand how brands compete in this new ch

Industrial-Instruction: An End-to-End Framework for Building Instruction-Tuning and Benchmark Datasets from Industrial Technical Reports

arXiv:2608.22817v1 Announce Type: new Abstract: Industrial technical reports contain high-value knowledge for maintenance, troubleshooting, and product engineering, but their heterogeneous structure (