Search: “model-releases”

CodeTaste: Can LLMs Generate Human-Level Code Refactorings?

arXiv:2603.04177v2 Announce Type: replace-cross Abstract: LLM coding agents can generate working code, but their solutions often accumulate complexity, duplication, and architectural debt. Human devel

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ComplexConstraints and Beyond: Expert Rubrics for RLVR

DGX agent

arXiv:2606.09118v1 Announce Type: new Abstract: As LLM capabilities advance rapidly, the evaluation methods used to assess them increasingly lag behind. Traditional benchmarks relied on programmatic v

model-releasesarxiv-cs-ai

9 Jun 2026

Component Ablation for Efficient Hybrid Language Model Architectures: Performance, Resilience, and Compression Implications

arXiv:2603.22473v2 Announce Type: replace-cross Abstract: Hybrid language models combine softmax attention with linear-time sequence mechanisms such as state-space or linear-attention layers, but the

Conan-embedding-v3: Fusing Modality-Specific Models for Omni-Modal Embedding

arXiv:2606.09331v1 Announce Type: cross Abstract: Omni-modal retrieval promises a single embedding space for text, image, video, document, and audio inputs, but building such a unified retriever is di

Condition-Gated Reasoning for Context-Dependent Biomedical Question Answering

arXiv:2602.17911v3 Announce Type: replace-cross Abstract: Current biomedical question answering (QA) systems often assume that medical knowledge applies uniformly, yet real-world clinical reasoning is

Conditional Normalizing Flows for Forward and Backward Joint State and Parameter Estimation

arXiv:2601.07013v2 Announce Type: replace-cross Abstract: Traditional filtering algorithms for state estimation -- such as classical Kalman filtering, unscented Kalman filtering, and particle filters

Context Rot in AI-Assisted Software Development: Repurposing Documentation Consistency for AI Configuration Artifacts

arXiv:2606.09090v1 Announce Type: cross Abstract: Developers increasingly provide AI coding assistants with persistent context through configuration files such as CLAUDE.md, AGENTS.md, and .cursorrule

ContextShift: A Controlled Benchmark for Context Dependence in Object Detection

arXiv:2606.09495v1 Announce Type: new Abstract: Modern object detectors achieve strong performance on standard benchmarks, yet their robustness to contextual variation remains insufficiently understoo

Convergence Bound and Critical Batch Size of Muon Optimizer

arXiv:2507.01598v5 Announce Type: replace Abstract: Muon, a recently proposed optimizer that leverages the inherent matrix structure of neural network parameters, has demonstrated strong empirical per

Convolutional Sparse Coding via the Locally Competitive Algorithm on Loihi 2

arXiv:2606.08584v1 Announce Type: new Abstract: Sparse coding provides a principled framework for signal representation by expressing an input as a linear combination of only a small number of basis f

Correcting Mean Bias in Text Embeddings: A Refined Renormalization with Training-Free Improvements on MMTEB

arXiv:2511.11041v2 Announce Type: replace-cross Abstract: We find that current sentence-embedding models produce outputs with a consistent bias: every embedding e decomposes as ilde e + mu, where the

Correlation Is Not Enough: Embedding Human Metadata for Individual Causal Discovery

arXiv:2606.09672v1 Announce Type: new Abstract: Ask a pretrained biomedical language model whether 'cortisol 28 ug/dL' and 'stock-market volatility' are related, and it returns a cosine similarity of

Counterfactual Transport Flows for Offline Conservative Trajectory Refinement

arXiv:2606.09115v1 Announce Type: new Abstract: Offline reinforcement learning (RL) offers a path to policy improvement from logged data alone, using historical returns or other measurable outcomes as

CoVEBench: Can Video Editing Models Handle Complex Instructions?

arXiv:2606.08415v1 Announce Type: cross Abstract: While recent text-guided video editing models excel at elementary tasks (e.g., style transfer, object insertion), real-world user requests are highly

CRANE: Knowledge Editing for Reasoning MLLMs

arXiv:2606.09033v1 Announce Type: new Abstract: The emergence of reasoning multimodal large language models (MLLMs), which generate explicit chain-of-thought (CoT) reasoning before producing answers,

Cross-View Urban Traffic Dataset: Drone-Supervised Ground Truth for Monocular Bird's-Eye View Localization

arXiv:2606.07708v1 Announce Type: cross Abstract: We introduce a dataset and benchmark for cross-view urban traffic perception built from synchronized ego-centric bicycle videos and aerial drone video

CTS-Bench: Benchmarking Graph Coarsening Trade-offs for GNNs in Clock Tree Synthesis

arXiv:2602.19330v2 Announce Type: replace Abstract: Graph Neural Networks (GNNs) are increasingly explored for physical design analysis in Electronic Design Automation, particularly for modeling Clock

Curvature-Guided LoRA: Matching Full Fine-Tuning in Function Space

arXiv:2603.29824v2 Announce Type: replace Abstract: Parameter-efficient fine-tuning methods such as LoRA enable efficient adaptation of large pretrained models, but often lag behind full fine-tuning i

DAL-PCQA: Enabling Distortion-Level and Language-Driven Reasoning for Point Cloud Quality Assessment

arXiv:2606.07938v1 Announce Type: new Abstract: Point Cloud Quality Assessment (PCQA) methods typically predict scalar Mean Opinion Scores (MOS), which quantify overall perceptual degradation but do n

Data Synthesis and Parameter-Efficient Fine-Tuning for Low-Resource NMT: A Case Study on Q'eqchi' Mayan

arXiv:2606.09767v1 Announce Type: cross Abstract: Neural machine translation for digitally low-resource Indigenous languages is often hindered by extreme data scarcity, prompting reliance on extractiv

De novo molecular generation with optical property preconditioning at the token level

arXiv:2606.08221v1 Announce Type: new Abstract: Designing OLED molecules with targeted optical properties remains challenging due to the scarcity of high-quality data and the limited reliability of co

Decision-Aware Memory Cards: Counterfactual-Inspired Context Selection and Compression for Tool-Using LLM Agents

arXiv:2606.08151v1 Announce Type: new Abstract: Tool-using LLM agents often fail not because relevant text is absent, but because decisive evidence is not selected, compressed, or surfaced at action t

Declarative Outcome-Conformant Synthesis: Exact, Closed-Form Specification Satisfaction and a Conformance Benchmark

arXiv:2606.08736v1 Announce Type: new Abstract: We study a capability the dominant paradigm in synthetic tabular data does not provide: exact satisfaction of a declared analytical outcome with no sour

Decoding Pedestrian Crossing Intention from Egocentric Vision via Vision Language Models

arXiv:2606.09142v1 Announce Type: cross Abstract: Egocentric vision offers a first-person view of human perception and decision making, yet its potential for traffic-safety prediction remains underexp

Decomposable Neuro Symbolic Regression

arXiv:2511.04124v3 Announce Type: replace Abstract: Symbolic regression (SR) models complex systems by discovering mathematical expressions that capture underlying relationships in observed data. Howe

Deep Tree Tensor Networks

arXiv:2502.09928v2 Announce Type: replace-cross Abstract: Originating in quantum physics, tensor networks (TNs) have been widely adopted as exponential machines and parametric decomposers for recognit

DeepMine-Mamba: Mitigating Information Dilution in Mamba-Based State Space Models for Document Image Binarization

arXiv:2606.08781v1 Announce Type: new Abstract: Document image binarization aims to separate foreground text from degraded backgrounds while preserving thin, broken, and low-contrast strokes. Although

Defending Against Malicious Finetuning by Scaling Train-time Adversarial Attacks

arXiv:2606.07970v1 Announce Type: cross Abstract: Current open-weight large language models (LLMs) are prone to malicious finetuning attacks, which could compromise the safety alignment of LLMs with o

Dendrograms of Mixing Measures for Softmax-Gated Gaussian Mixture of Experts: Consistency Without Model Sweeps

arXiv:2510.12744v2 Announce Type: replace-cross Abstract: We develop a unified statistical framework for softmax-gated Gaussian mixture of experts (SGMoE) that addresses three long-standing obstacles

Developing Distance-Aware Physics-Constrained Probabilistic Frameworks for Industrial Prognostics

arXiv:2512.08499v3 Announce Type: replace-cross Abstract: Development of reliable and physically interpretable probabilistic frameworks for industrial prognostics remain nascent, and existing literatu

DHAuDS: A Dynamic and Heterogeneous Audio Benchmark for Test-Time Adaptation

arXiv:2511.18421v2 Announce Type: replace-cross Abstract: Existing Test-time Adaptation (TTA) studies rely heavily on static and homogeneous corruption protocols, such as ImageNet-C and CIFAR-10-C/100

DICE: Entropy-Regularized Equilibrium Selection for Stable Multi-Agent LLM Coordination

arXiv:2606.08068v1 Announce Type: new Abstract: Multi-agent large language model (LLM) systems often fail to reliably outperform a single strong model equipped with best-of-N sampling. We argue that a

DisCo: World Models with Discrete Camera Motion Control

arXiv:2606.07967v1 Announce Type: new Abstract: Controllable video world models target interactive world exploration, where models must faithfully execute explicit action commands while preserving vis

Discovering heuristics in a complex SAT solver with large language models

arXiv:2507.22876v2 Announce Type: replace Abstract: The Satisfiability problem (SAT) is fundamental in computational complexity theory and has a wide range of industrial applications. Optimizing moder

Distilling Safe LLM Systems via Soft Prompts for On Device Settings

arXiv:2606.09388v1 Announce Type: new Abstract: Deploying safe large language models (LLMs) on resource-constrained edge devices presents a critical challenge: while dual-model systems combining LLMs

Distortion-Aware PETR for BEV Object Detection with Mixed Pinhole-Fisheye Cameras

arXiv:2606.08680v1 Announce Type: new Abstract: Fisheye cameras are widely deployed in autonomous driving perception suites for their low cost and full-coverage field of view (FOV), yet their potentia

DIYHealth Suite: Dataset, Model, and Benchmark for Health Management at Home

arXiv:2606.07542v1 Announce Type: cross Abstract: Generative AI is reshaping healthcare, yet most existing advances rely on hospital-grade devices, which limits their accessibility and potential for h

Domain-Adapted Small Language Models with Hybrid Post-Processing: Achieving Cost-Efficient, Low-Latency Multi-Label Structured Prediction via LoRA Fine-Tuning on Scarce Data

arXiv:2606.05781v2 Announce Type: replace Abstract: Deploying frontier large language models (LLMs) for domain-specific structured evaluation tasks incurs prohibitive latency, cost, and data-privacy o

DriveReward: A Comprehensive Dataset and Generative Vision-Language Reward Model for Autonomous Driving

arXiv:2606.08525v1 Announce Type: new Abstract: Reward models play a pivotal role in reinforcement learning (RL) and multi-modal trajectory selection for autonomous driving. However, acquiring such re

Driving Video Retrieval for Complex Queries with Structured Grounding

arXiv:2606.09109v1 Announce Type: new Abstract: Video retrieval at scale is central to data curation and safety validation in autonomous driving, where users want to find not only scenes but also dyna

Dual Quaternion-Based Unscented Kalman Filter with Visual Inertial Odometry for Navigation in GPS-Denied Environments

model-releasesarxiv-cs-ro

arXiv:2606.09292v1 Announce Type: new Abstract: Reliable navigation in GPS-denied environments remains a fundamental challenge in robotics, aerospace, and autonomous vehicle applications. This paper p

Echo-DM: Ultrasound Marker Removal via Conditional Latent Diffusion and Region-Aware Fusion

arXiv:2606.09378v1 Announce Type: new Abstract: Clinical ultrasound images often contain artificial markers, such as measurement calipers and text, to assist diagnostic interpretation and comparison.

Efficient Minimal Solvers for Relative Pose Estimation in Autonomous Driving Applications

arXiv:2606.09569v1 Announce Type: cross Abstract: With the advancement of visual sensing systems, computer vision is playing an increasingly important role in autonomous driving and robot navigation.

Efficient Minimal Solvers for Visual-Inertial Relative Pose Estimation in Multi-Camera Systems

arXiv:2606.09477v1 Announce Type: new Abstract: Estimating the relative poses of multi-camera systems is a fundamental problem in computer vision, with critical applications in autonomous vehicles, mo

EgoTactile: Learning Grasp Pressure for Everyday Objects from Egocentric Video

arXiv:2606.09243v1 Announce Type: cross Abstract: Estimating full-hand grasp pressure from egocentric video is critical for immersive VR and robotic manipulation, yet dense tactile sensing often relie

Emergence World: A Platform for Evaluating Long-Horizon Multi-Agent Autonomy

arXiv:2606.08367v1 Announce Type: cross Abstract: Most evaluations of LLM agents look like exams: a discrete task, a clean environment, a score in minutes or hours. We argue that this approach is mism

End-to-End Context Compression at Scale

arXiv:2606.09659v1 Announce Type: cross Abstract: Long-context language model inference is bottlenecked by memory, as the KV cache grows with context length. Recent techniques to compress the KV cache

End-to-End Training for Discrete Token LLM based TTS System

arXiv:2606.09234v1 Announce Type: cross Abstract: Recent state-of-the-art (SOTA) text-to-speech (TTS) systems typically adopt a cascaded pipeline consisting of a speech tokenizer, an autoregressive la