model releases

SleuthBench: Benchmarking Statistical LLM Evaluation Using Tabular Hidden Signals

arXiv:2609.34228v1 Announce Type: new Abstract: Evaluating statistical discovery by large language model (LLM) agents requires verifiable analytical ground truth. Establishing such ground truth for re

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Model Releases

SlimWise: Decoupling Expert Pruning Across Prefill and Decode for Efficient MoE Serving

DGX agent

arXiv:2609.34117v1 Announce Type: new Abstract: Mixture-of-experts (MoE) models activate few experts per token, yet batched decoding can access nearly the entire expert pool, making expert-weight traf

model-releasesarxiv-cs-lg

29 Sept 2026

SMAT: Simple and Efficient Merge-Aware Training

arXiv:2609.33437v1 Announce Type: new Abstract: Model merging integrates the capabilities of multiple experts without joint retraining, but standard expert training optimizes task loss alone and does

SMORE: Stability-Promoting Mesh-Agnostic Model Reduction for Time-Dependent PDEs

arXiv:2609.33205v1 Announce Type: new Abstract: High-fidelity simulations of time-dependent partial differential equations (PDEs) are computationally expensive, motivating data-driven reduced-order su

SOLAR: A State-Driven Online Learning Rate Scheduler for LLM Pretraining

arXiv:2609.34681v1 Announce Type: new Abstract: Learning-rate (LR) scheduling plays a central role in large language model (LLM) pretraining, yet current practice still relies heavily on hand-crafted

SOLO: Pretraining Billion-Parameter Language Models with Shared-Output Local Learning

arXiv:2609.35440v1 Announce Type: new Abstract: Large language models are trained with backpropagation, whose global gradient coordinates all layers but forces each to hold its activations and wait fo

SolveEdit: Benchmarking Visual Problem Solving in Generative Models

arXiv:2609.35504v1 Announce Type: new Abstract: Machine intelligence is often evaluated through abstract reasoning problems, yet many real-world problems are visual, such as arranging objects, repairi

Source-Lifted Flow Matching for Intervenable Multimodal Imitation

model-releasesarxiv-cs-ro

arXiv:2607.10206v2 Announce Type: replace Abstract: Flow-matching policies are promising for imitation learning because they model complex multimodal action distributions. However, their stochasticity

SPACE-LoRA: Allocating Activation-Subspace Protection for Continual Learning

arXiv:2609.34453v1 Announce Type: new Abstract: This study addresses the catastrophic forgetting problem that occurs when sequentially learning successive tasks using Low-Rank Adaptation (LoRA) from a

SPACE: Sparse Predictive Attractor via Counterfactual Eviction for Streaming Video Memory

arXiv:2609.32592v1 Announce Type: new Abstract: Fixed-capacity streaming video memory requires repeated eviction decisions whose effects accumulate over time. Yet existing policies are evaluated prima

Spatial Grafting: Grounding 3D Features for Flow-Matching Robot Policies

arXiv:2609.35249v1 Announce Type: cross Abstract: Pretrained robot manipulation policies such as vision-language-action models (VLAs) or world-action models (WAMs) leave interaction-relevant metric ge

Spectral Reversal: Counteracting Singular Value Bias for Graph Prompting

arXiv:2609.32143v1 Announce Type: new Abstract: Pre-training Graph Neural Networks (GNNs) via self-supervised learning has become a dominant paradigm, yet efficiently adapting frozen encoders remains

SR4-Fit: A Unified Interpretable Rule-Based Machine Learning Framework for Informative and Trustworthy Decision-Making

arXiv:2609.34019v1 Announce Type: new Abstract: In many high-stakes applications, machine learning is dominated by black-box models that require post hoc explanations to justify their predictions. The

SRHarness: A Harness for Agentic Symbolic Regression

arXiv:2609.35501v1 Announce Type: cross Abstract: Recent agentic symbolic regression approaches increasingly rely on large language models to analyze data, select scientific operations, and refine hyp

Stabilizing the Dynamic Low-Rank Training

arXiv:2609.32615v1 Announce Type: new Abstract: Training neural networks directly in a low-rank parameterization is an appealing route to reducing memory, compute, and storage simultaneously during bo

Stashbird: Efficient Speaker-Indexed Memory for Conversational Agents

arXiv:2609.34242v1 Announce Type: cross Abstract: AI agents require memory that preserves information across user-agent exchanges, user-to-user conversations, and group conversations with or without a

StegGNN: Learning Graphical Representation for Image Steganography

arXiv:2609.32362v1 Announce Type: new Abstract: Image steganography refers to embedding secret messages within cover images while maintaining imperceptibility. Recent advances in deep learning - prima

STeP: Signal Temporal Logic for Precise Specifications for Action Generation with Vision Language Models

model-releasesarxiv-cs-ro

arXiv:2607.18580v2 Announce Type: replace Abstract: Natural-language robot instructions often specify more than a coarse task goal: they may impose spatial, temporal, and logical requirements that mus

Stochastic Engrams for Efficient Continual Learning

arXiv:2503.21436v2 Announce Type: replace Abstract: The ability to learn continuously in artificial neural networks (ANNs) is often limited by catastrophic forgetting, a phenomenon in which new knowle

StoryEngine: A State-Grounded Agentic Framework for Video Storytelling

arXiv:2609.33627v1 Announce Type: new Abstract: Despite recent progress in agentic multi-shot video generation, producing coherent and consistent long-form stories remains challenging. Existing agenti

STR: Supervised Transcoder Replacement for Reducing Steering Side Effects

arXiv:2609.32519v1 Announce Type: cross Abstract: Model steering can strengthen a target behavior while degrading other useful behaviors. We introduce Supervised Transcoder Replacement (STR) to reduce

STRIDE: State-Transition Representation via Increment Dynamics and Evolution

arXiv:2609.32367v1 Announce Type: new Abstract: We introduce STRIDE (State-Transition Representation via Increment Dynamics and Evolution), which defines states through derivative fingerprints and lea

Structure-First Point Cloud Learning with Mapper Region Graphs

arXiv:2602.05522v2 Announce Type: replace Abstract: Robust 3D point cloud classification is often pursued by scaling up backbones or relying on specialized data augmentation. We instead ask whether st

Superquadric Primitive Decomposition of 3D point clouds via Geometric-Aware Inlier Refinement

arXiv:2609.35725v1 Announce Type: new Abstract: The decomposition of 3D point clouds into interpretable geometric primitives remains a longstanding challenge in Computer Vision and Computer Graphics.

SV2V-RSim: A Comprehensive Benchmark for Self-Selective V2V Cooperative Perception with Near-Realistic Data

arXiv:2609.32863v1 Announce Type: new Abstract: Vehicle-to-Vehicle (V2V) cooperative perception enhances autonomous driving by enabling vehicles to share information beyond their direct line of sight.

SwingRL: Adaptive Observation Reinforcement Learning with World-Model Prediction for Cable-Suspended Hoisting Control

model-releasesarxiv-cs-ro

arXiv:2609.33053v1 Announce Type: new Abstract: Cable-suspended hoisting is widely used to move heavy or bulky payloads that cannot be handled conveniently by rigid pick-and-place systems, for example

SWT: Self-Supervised Video Object Segmentation via Sliding, Wavelet and Transportation

arXiv:2609.31725v1 Announce Type: new Abstract: Video Object Segmentation (VOS) aims to accurately segment target objects from consecutive video frames and track the changes of the objects in each fra

SymbolicArena: A Unified Infrastructure for Benchmark Distillation and Dynamic Evaluation in Symbolic Regression

arXiv:2609.35113v1 Announce Type: new Abstract: Symbolic regression (SR) seeks concise and interpretable mathematical expressions from data for scientific equation discovery. Existing SR benchmarks fa

Symmetry-quotient Flatness and Generalization

arXiv:2609.31634v1 Announce Type: new Abstract: This paper develops a theorem-level pipeline in symmetry-quotient settings: quotient linear stability implies quotient flatness, quotient flatness impli

SynCo: Learning Cross-Modal Synergy by Contrasting Interaction Residuals

arXiv:2609.32846v1 Announce Type: new Abstract: Multimodal contrastive learning is a dominant paradigm for learning transferable representations from unlabeled data, but standard objectives primarily

SyncRA: Learning Temporal Correspondence in Omni-Modal Models

arXiv:2609.34363v1 Announce Type: new Abstract: Recent omni-modal models demonstrate strong perception of audio and visual inputs, yet often struggle to connect what they hear with what they see at th

SynDORBench: Evaluating LVLM Perceptual Robustness Under Physically Constrained Visibility Conditions

arXiv:2609.31823v1 Announce Type: new Abstract: Large vision-language models (LVLMs) have demonstrated remarkable performance on multimodal reasoning benchmarks, yet their perceptual reliability under

Synergizing Discriminative Exemplars and Self-Refined Experience for MLLM-based In-Context Learning in Medical Diagnosis

arXiv:2603.27737v2 Announce Type: replace Abstract: General Multimodal Large Language Models (MLLMs) often underperform in capturing domain-specific nuances in medical diagnosis, trailing behind fully

Synthetic data for ratemaking: imputation-based methods vs adversarial networks and autoencoders

arXiv:2509.02171v3 Announce Type: replace-cross Abstract: Actuarial ratemaking depends on high-quality data, yet access to such data is often limited by the cost of obtaining new data, privacy concern

Teach to Learn: Hint Annealing for Self-improving LLM Reasoning

arXiv:2609.34975v1 Announce Type: new Abstract: Group Relative Policy Optimization (GRPO) improves language-model reasoning by comparing verified rewards among multiple solution rollouts for each quer

Temporal Modelling for Burn Scars on Sentinel-3

arXiv:2609.34596v1 Announce Type: new Abstract: Rapid and accurate burn scar delineation from satellite imagery is essential for post-fire damage assessment. Sentinel-3 OLCI, with daily revisit and 21

TerMeZO: Ternary Sparse Zeroth-Order Optimization for Fine-tuning BitNet Models at the Edge

arXiv:2609.33548v1 Announce Type: new Abstract: Fine-tuning anguage models (LLMs) with first-order optimizers requires a memory several times larger than that required for inference. Memory-efficient

Terminal-Register Certification for Finite-Measurement Learning of Multiscale Quantum States

arXiv:2609.33567v1 Announce Type: cross Abstract: Structured quantum-state learning not only depends on an expressive ansatz but also on an operational certificate that stays meaningful with finite me

Test-Time Spatial Reasoning for Robot Manipulation Using Generative Real-to-Sim

arXiv:2609.33982v1 Announce Type: cross Abstract: Spatial reasoning is fundamental to general robot intelligence, as it enables robots to complete long-horizon tasks involving multi-object interaction

Tetra: Serving Leech-Lattice Quantized LLMs at 2.7 Bits per Parameter

arXiv:2609.35465v1 Announce Type: new Abstract: Leech-lattice quantization gives good quality at two bits per weight, but its codebooks hold more than 10^14 points, too many for a lookup table. Our ea

TGRL: Temperature-Grouped Reinforcement Learning for Efficient Exploration in LLMs

arXiv:2609.33589v1 Announce Type: new Abstract: Efficient exploration often remains a central bottleneck in reinforcement learning with verifiable rewards (RLVR). Although temperature control and test

Thanks to you r/LocalLLaMA, my mom was able to use my app! The open-source app that can watch your screen and trigger actions. It is now easy to use, thanks to your feedback.

model-releasesr-localllama

TL;DR: I'm a solo dev who wanted a simple, private way to have local LLMs watch my screen and do simple logging/notifying. After a year of building, I released v3.0.0 and my mom was able to use it for

The cost of useful natural gradient updates

arXiv:2609.33499v1 Announce Type: new Abstract: What information is needed to turn a natural-gradient direction into a useful finite update? Under a population Kullback-Leibler (KL) budget, we call a

The Devil in the Details: Emergent Misalignment, Format and Coherence in Open-Weights LLMs

arXiv:2511.20104v2 Announce Type: replace Abstract: Prior work has shown that fine-tuning models on a narrow domain with misaligned data can lead to broad misalignment - a phenomenon termed 'emergent

The Earth in One Gaze: Training-Free Active Focus for UHR Remote Sensing Understanding

arXiv:2609.31747v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) must balance local detail against scene context when interpreting ultra-high-resolution (UHR) remote sensing (R

The Future of Claude Code: Mods, Mutable Software, Pacing the Frontier, & Multiplayer Agents with Thariq Shihipar https://latent.space/p/tha…

The Future of Claude Code: Mods, Mutable Software, Pacing the Frontier, & Multiplayer Agents with Thariq Shihipar https://latent.space/p/thariq @AnthropicAI’s @trq212 explains why prompting is still o

model-releasesswyx--x

The GUI Is Not the State: Diagnosing State Aliasing in GUI World Models

arXiv:2609.32679v1 Announce Type: cross Abstract: GUI World Models (GUI-WMs) are increasingly used to predict future states for agent planning and simulation, yet most existing formulations condition

The Low-Rank Structure of VLA Reinforcement Learning

arXiv:2609.34599v1 Announce Type: new Abstract: Reinforcement learning (RL) is increasingly used to post-train vision-language-action (VLA) models, yet how RL reshapes these policies remains poorly un