Search: “model-releases”

Probabilistic Symbolic Regression for Equation Discovery via Operator-induced and Regularized Symbolic Forests

arXiv:2509.19710v2 Announce Type: cross Abstract: Symbolic regression has emerged as a powerful tool for artificial intelligence-driven scientific discovery by learning interpretable analytical expres

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Model Releases

RDQ: Residual Distribution Quantization for Large Language Models

DGX agent

arXiv:2607.10137v2 Announce Type: replace Abstract: Post-training quantization (PTQ) of large language models degrades sharply below 4-bit precision. We identify the root cause as residual stream dist

model-releasesarxiv-cs-lg

29 Jul 2026

RDVSv2: A Large-scale Benchmark for RGB-D Video Salient Object Detection

arXiv:2607.25392v1 Announce Type: new Abstract: We introduce RDVSv2, a large-scale benchmark for RGB-D video salient object detection (RGB-D VSOD) with dense frame-level annotations. Existing datasets

ReDesign: Recovering Editable Design Structures from Images via Agentic Decomposition

arXiv:2607.25565v1 Announce Type: new Abstract: Recovering an editable design file from a raster image is a common and costly bottleneck in modern design workflows, yet remains challenging since edita

RefBench-PRO: Perceptual and Reasoning Oriented Benchmark for Referring Expression Comprehension

arXiv:2512.06276v3 Announce Type: replace-cross Abstract: Referring Expression Comprehension (REC) is a vision-language task that localizes a specific image region based on a textual description. Exis

Reference Traces for Auditing Invisible Weight Updates and Guiding Exact-Budget Protection

arXiv:2607.09800v3 Announce Type: replace Abstract: Direct low-precision write-back can erase optimizer proposals, while aggregate update visibility need not identify parameters worth protecting. We s

Regime-Adaptive Bayesian Optimization via Dirichlet Process Mixtures of Gaussian Processes

arXiv:2601.20043v2 Announce Type: replace Abstract: Standard Bayesian Optimization (BO) assumes uniform smoothness across the search space an assumption violated in multi-regime problems such as molec

Reinforcement Learning for Code Optimization

arXiv:2607.25970v1 Announce Type: cross Abstract: RL for code correctness is now established: have the model generate a program, run it against hidden test cases, and reward solutions that pass. Exten

ReLATE: Reliability-Guided Evidence Fusion for Robust UAV--Satellite cross-view Geo-Localization

arXiv:2607.25524v1 Announce Type: cross Abstract: Unmanned aerial vehicle (UAV)-satellite cross-view geo-localization matches UAV images against satellite imagery and has achieved impressive accuracy

REPREC: Representation Driven Parameter-Efficient Recommendation System

arXiv:2607.24845v1 Announce Type: cross Abstract: Large language models (LLMs) have been applied to sequential recommendation by formulating it as a natural language task. Previous work has improved p

Research Report on Noise-Shaped One-Bit Coefficients in Discrete Polynomial Fourier Extension

arXiv:2607.24868v1 Announce Type: new Abstract: This report studies noise-shaped one-bit coefficients in normalized discrete polynomial Fourier extension. For first-order Sigma-Delta quantization, the

Rethinking CD: A Reproducibility Study and Extension on the Ineffectiveness of Contrastive Decoding at Mitigating Object Hallucinations in MLLMs

arXiv:2607.25196v1 Announce Type: new Abstract: Contrastive decoding (CD) has been proposed as a training-free strategy for mitigating object hallucinations in multimodal large language models (MLLMs)

Retraction-Free Optimization over the Stiefel Manifold for the LoRA Fine-Tuning

arXiv:2607.25299v1 Announce Type: cross Abstract: Optimization over the Stiefel manifold plays a significant role in various machine learning tasks. Existing methods either use the retraction operator

RIDGE: An Autonomous Framework for Validation and Method Discovery in LLM-Generated Option Pricing

arXiv:2607.25199v1 Announce Type: cross Abstract: Automated code generation is becoming an important tool in quantitative finance, where large language models can generate option pricing implementatio

RoboProcessBench: Benchmarking Process-Aware Understanding in Vision-Language Robotic Manipulation

model-releasesarxiv-cs-ro

arXiv:2606.13040v2 Announce Type: replace Abstract: Vision-language models (VLMs) are increasingly explored as visual critics, reward generators, and failure detectors in robotic manipulation. These r

RRS-10K: A Multitask Vision-Language Model Benchmark for Rare Remote Sensing Image Interpretation

arXiv:2607.24810v1 Announce Type: new Abstract: Vision-language models (VLMs) have achieved strong performance on general remote sensing tasks. However, their capability for rare scenes remains insuff

RSIBench-Data: Benchmarking Data-Centric Research for Recursive Self-Improvement

arXiv:2607.25886v1 Announce Type: cross Abstract: Recursive self-improvement requires turning evidence of model failures into better models. Data-centric post-training research entails diagnosing capa

RSMeM: Knowledge-Enhanced Memory Evolution for Remote Sensing Agents with Systematic Evaluation

arXiv:2607.24772v1 Announce Type: new Abstract: Geoscience research requires complex analysis and domain expertise, with remote sensing (RS) observations as a key foundation. However, existing RS agen

SAGE: Stochastic Prompt Optimization via Agent-Guided Exploration

arXiv:2606.18902v2 Announce Type: replace Abstract: Context engineering has emerged as a primary lever for improving AI systems without parameter updates. Recent work showing that textual gradients do

SAM-MI: A Mask-Injected Framework for Enhancing Open-Vocabulary Semantic Segmentation with SAM

arXiv:2511.20027v2 Announce Type: replace Abstract: Open-vocabulary semantic segmentation (OVSS) aims to segment and recognize objects universally. Trained on extensive high-quality segmentation data,

ScaleResfusion: Residual Rectified Flow based on Residual Vector Field

arXiv:2607.25275v1 Announce Type: cross Abstract: Real-world Image Restoration (Real-IR) aims to recover high-quality (HQ) images from complex and unknown degradations. Although recent diffusion-based

ScoreShield: Differentially Private Release of Similarity Scores

arXiv:2607.25041v1 Announce Type: cross Abstract: A growing number of applications, such as biometrics and retrieval-augmented generation (RAG), rely on cosine similarity scores computed between vecto

SecDrift: Measuring Sector-Conditioned Security Drift in AI-Generated Code

arXiv:2607.25225v1 Announce Type: cross Abstract: LLMs are increasingly used for code generation in critical infrastructure, yet the security effect of domain-specific prompting is understudied. We pr

Sense it with your eyes: Sensation Generation and Understanding for Advertisements

arXiv:2607.25314v1 Announce Type: new Abstract: Sensory advertising evokes human senses through visual cues, enabling audiences to mentally simulate experiences and increasing persuasive impact. Despi

SGTP: Sampling-based Game-Theoretic Planning for Real-Time Multi-Vehicle Autonomous Racing

model-releasesarxiv-cs-ro

arXiv:2607.25388v1 Announce Type: new Abstract: Autonomous multi-vehicle racing requires real-time planning of diverse competitive behaviors in intense interactions. Existing planners often struggle t

Sharpness-Aware Minimization and Muon: Robustness under the Spectral Norm

arXiv:2607.26001v1 Announce Type: new Abstract: Sharpness-Aware Minimization (SAM) aims to improve generalization by encouraging insensitivity to small, worst-case parameter perturbations. However, th

Sharpness-aware Model Merging with Salience Recovery for LLM-based Cross-Domain Sequential Recommendation

arXiv:2607.25366v1 Announce Type: cross Abstract: LLM-based Cross-Domain Sequential Recommendation (CDSR) leverages LLMs to enhance target performance via deep semantic reasoning, alleviating the depe

Shieldstral

arXiv:2607.25857v1 Announce Type: new Abstract: We introduce Shieldstral, a 3B-parameter policy-adaptive multimodal safety classifier that matches or outperforms models nearly 7imes its size on text s

Similar Models Learn Differently: Final-Window Pretraining Shapes Post-Training Beyond SFT

arXiv:2607.25063v1 Announce Type: new Abstract: Developers judge a model checkpoint by how it behaves. After supervised fine-tuning (SFT), two checkpoints that perform about the same across relevant b

Simulation-based parameter estimation via a combination of embedded normalizing flows and implied empirical probabilities under moment restrictions

arXiv:2607.25026v1 Announce Type: cross Abstract: In this work, we present a simulation-based parameter estimation framework for a model defined by a computational simulation of a physical system. We

SpecPrefetch: Parameter-Efficient Expert Prefetching for Sparse MoE Foundation Models

arXiv:2607.24787v1 Announce Type: new Abstract: Sparse Mixture-of-Experts (MoE) models expand foundation model capacity through conditional expert activation, but their full expert pools remain diffic

SpeechLLM Meets Federated Learning for End-to-End ASR: English and Italian Case Studies

arXiv:2607.25716v1 Announce Type: new Abstract: Federated learning (FL) enables privacy-preserving training of automatic speech recognition (ASR) systems across distributed data sources, yet its appli

Spend Experts Where You Are Unsure: Confidence-Adaptive Routing for Mixture-of-Experts LoRA

arXiv:2607.26052v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) variants of Low-Rank Adaptation (LoRA) route every token to a fixed number of experts k. Tokens differ in how uncertain the mod

SurgSLOT: Segment Anything in Surgical Videos via Semantic Long-term Tracking

arXiv:2511.16618v2 Announce Type: replace Abstract: Surgical scene understanding demands temporally consistent tracking of instruments and tissues. For clinical use, such tracking should generalize to

TabRank: Chain-of-Thought Distillation for Table Re-Rankers

arXiv:2607.25182v1 Announce Type: cross Abstract: The ability to retrieve relevant tables for answering questions is a key task for structured information retrieval. Multi-stage retrieval systems rely

Three Sides of Retrieval: Factorial Evidence for Document-Side, Query-Side, and Answer-Side Complementarity in RAG

arXiv:2607.24781v1 Announce Type: cross Abstract: RAG systems rely on chunking, which destroys structural information in documents. Existing heading-based retrieval (Jeong et al., 2025) requires multi

TimeCapsule: Generative Hallucination as a Method for Historical Sensemaking

arXiv:2607.24750v1 Announce Type: new Abstract: Large Language Models (LLMs) are temporally overexposed: trained on vast contemporary corpora, they encode present-day concepts that make them unreliabl

Tokenizing Numerical and Embedding Features for LLM RecSys

arXiv:2607.10016v2 Announce Type: replace-cross Abstract: Large language models (LLMs) are increasingly used as backbone architectures for recommender systems because of their strong sequence modeling

TopoGR: Revealing and Preserving Latent Structure of Semantic ID in Generative Recommendation

arXiv:2607.25216v1 Announce Type: cross Abstract: Semantic ID-based generative recommendation tokenizes each item into a sequence of discrete semantic IDs and predicts the next item by generating sema

Toward an Organizational Science of Multi-Agent LLM Systems: Decoupling Who, How, and Which Algorithm

arXiv:2607.25446v1 Announce Type: new Abstract: Multi-agent frameworks built on large language models (LLMs) routinely entangle three logically distinct concerns: who is on the team (organization), ho

Towards Faithful Sentimental Image Captioning via Evidence-Aware Multi-Agent Reasoning

arXiv:2607.25789v1 Announce Type: new Abstract: Sentimental Image Captioning (SIC) requires balancing emotional expression with visual fidelity. Existing methods often struggle with this trade-off, le

Towards Real-World RUL Prediction for Aircraft Compressors Under Variable Conditions with Physics-Guided Domain Adaptation

arXiv:2607.24809v1 Announce Type: cross Abstract: Remaining useful life prediction for aircraft centrifugal air compressors in real commercial operations poses challenges that controlled benchmark dat

Towards Robust Reinforcement Learning for Small-Scale Language Model Agents

arXiv:2607.25091v1 Announce Type: new Abstract: The alignment of Small Language Models (SLMs) in the 70--500M parameter range using reinforcement learning is often considered unstable, though the unde

Towards Understanding the Cognitive Habits of Large Reasoning Models

arXiv:2506.21571v3 Announce Type: replace-cross Abstract: Large Reasoning Models (LRMs), which autonomously produce a reasoning Chain of Thought (CoT) before producing final responses, offer a promisi

Track-Leakage-Free Hold-Out Self-Validation for Photogrammetric Reconstruction: Protocol, Sensitivity, and Limits

arXiv:2607.24852v1 Announce Type: new Abstract: Automated photogrammetric inspection emits metric measurements from a 3D reconstruction whose own correctness is normally unknown without an external su

TWICE: Two-Clock, Two-Window Learning for Long-Horizon Conversion Prediction in Online Advertising

arXiv:2607.25404v1 Announce Type: new Abstract: Long-horizon conversion prediction under delayed feedback creates a two-clock, two-window learning problem in online advertising. A short base observati

Two Views, One Voice: Evidence-Grounded Conversational Music Recommendation

arXiv:2607.24846v1 Announce Type: cross Abstract: Traditional conversational recommenders entangle retrieval and response generation within a single text interface, so exact entity cues fade as the di

UniMem: Complementary Episodic-to-Parametric Memory for Boundary-Agnostic Task Streams

arXiv:2607.26017v1 Announce Type: new Abstract: Memory is essential for LLM agents to accumulate task experience and reuse task-specific execution strategies. However, real-world deployment over bound