Search: “model-releases”

Scaling Laws for Masked-Reconstruction Transformers on Single-Cell Transcriptomics

arXiv:2602.15253v2 Announce Type: replace Abstract: Neural scaling laws -- power-law relationships between loss, model size, and data -- have been extensively documented for language and vision transf

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Model Releases

scCBGM: Interpretable Single-Cell Counterfactual Editing

DGX agent

arXiv:2606.07760v1 Announce Type: new Abstract: Understanding cellular phenotypes and how they respond to perturbations is critical for disease biology and therapeutic design. Single-cell RNA sequenci

model-releasesarxiv-cs-lg

9 Jun 2026

SceneConductor: 3D Scene Generation from Single Image with Multi-Agent Orchestration

arXiv:2606.08402v1 Announce Type: cross Abstract: Generating complete 3D scenes from a single image requires inferring globally consistent geometry, object relationships, and environmental context fro

Sci-Rho: A Multilingual Visually-Grounded Symbolic Benchmark for STEM Problems

arXiv:2606.08034v1 Announce Type: cross Abstract: Symbolic benchmarks have emerged as a key approach to assess model robustness under minor modifications to STEM-related questions. However, existing s

SciFlow-Bench: Evaluating Structure-Aware Scientific Diagram Generation via Inverse Parsing

arXiv:2602.09809v2 Announce Type: replace Abstract: Scientific diagrams convey explicit structural information, yet modern text-to-image models often produce visually plausible but structurally incorr

See More, Think Deeper: Query-Expanded Visual Evidence and Answer-Clue Guided Reflection for Long Video Understanding

arXiv:2606.09064v1 Announce Type: cross Abstract: Recent advances in Video Large Language Models (Video-LLMs) have enabled performance on long-video understanding tasks. However, existing methods stil

SegmentAnyTreeV2: Scaling Transformer-Based Tree Instance Segmentation Across Sensors, Platforms, and Forests

arXiv:2606.08206v1 Announce Type: new Abstract: We present SegmentAnyTreeV2, a sensor- and platform-agnostic framework for semantic and instance segmentation of forest point clouds. The model combines

Semi-supervised Source Detection in Astronomical Images: New Benchmark and Strong Baseline

arXiv:2606.09219v1 Announce Type: new Abstract: Source detection in modern observational astronomy is a cornerstone for localizing and identifying stellar sources accurately. It is crucial for studies

SENTRY: Statistical Reliability Analysis of Vision Transformers Under Soft Errors

arXiv:2606.07620v1 Announce Type: cross Abstract: With the growth of Vision Transformers in safety-critical domains like autonomous systems and medical imaging, ensuring their reliability against soft

Seq103: A Unified Neuroevolution Framework for Compact Sequence Architecture Discovery

arXiv:2606.07664v1 Announce Type: cross Abstract: Neuroevolution is a representative neural architecture search paradigm that evolves both network topology and weights through evolutionary algorithms.

Shared Latent Structures Enable Unified Backdoor Detection and Mitigation in LLMs

arXiv:2606.07963v1 Announce Type: new Abstract: Backdoor attacks in large language models (LLMs) are often treated as isolated trigger-response failures, motivating defenses tailored to specific trigg

Shift-Dependent Asymmetry: Orthogonal Inverse Low-Rank Adaptation for Federated Medical Segmentation

arXiv:2606.08687v1 Announce Type: new Abstract: Low-Rank Adaptation (LoRA) enables efficient federated fine-tuning of segmentation foundation models for medical imaging. However, most federated LoRA m

Signals Are Not States: Neuro-Symbolic Safeguards for Culturally Aware Classroom AI

arXiv:2603.22793v2 Announce Type: replace Abstract: Classroom AI systems increasingly infer high-level educational states such as engagement, confusion, collaboration, participation, and instructional

SIMPLE: Simulation-Based Policy Learning and Evaluation for Humanoid Loco-manipulation

model-releasesarxiv-cs-ro

arXiv:2606.08278v1 Announce Type: new Abstract: Humanoid foundation models are advancing faster than we can evaluate them. While real-world testing is expensive and difficult to reproduce, existing si

SLMJury: Can Small Language Models Judge as Well as Large Ones?

arXiv:2606.07810v1 Announce Type: cross Abstract: Large language models (LLMs) are widely used as judges for evaluating model outputs, but their high cost, latency, and opacity limit scalability. We i

SNN-MLIR: An MLIR Dialect for Compiling Neuromorphic SNNs from NIR to Bare-Metal C

arXiv:2606.09213v1 Announce Type: cross Abstract: Spiking neural networks (SNNs) are increasingly trained in a wide range of frameworks (SnnTorch, Lava, Norse, and others) each with its own model form

SoK: Reconstruction Attacks on Synthetic Tabular Data (Insights from Winning the NIST CRC)

arXiv:2606.08372v1 Announce Type: cross Abstract: Synthetic data is increasingly promoted as a privacy-preserving substitute for releasing sensitive tabular records, yet its central adversarial threat

Solving Inverse Problems with Flow-based Models via Model Predictive Control

arXiv:2601.23231v2 Announce Type: replace-cross Abstract: Flow-based generative models provide strong unconditional priors for inverse problems, but guiding their dynamics for conditional generation r

Sparse Autoencoders Reveal Interpretable and Steerable Features in VLA Models

model-releasesarxiv-cs-ro

arXiv:2603.19183v2 Announce Type: replace Abstract: Vision-Language-Action (VLA) models have emerged as a promising approach for general-purpose robot manipulation. However, little research has mechan

SpatialWorld: Benchmarking Interactive Spatial Reasoning of Multimodal Agents in Real-World Tasks

arXiv:2606.09669v1 Announce Type: new Abstract: Spatial reasoning is a foundational capability for multimodal large language models (MLLMs) to perceive and operate within the physical world. However,

SpectrumKV: Per-Token Mixed-Precision KV Cache Transfer for Prefill-Decode Disaggregated LLM Serving

arXiv:2606.08635v1 Announce Type: new Abstract: Prefill-decode (PD) disaggregation decouples prompt processing from token generation, but it also turns the key-value (KV) cache into a network payload.

SSAFE: Simple and Strong AI-Generated Image Detection via Frozen Vision Encoders

arXiv:2606.08634v1 Announce Type: new Abstract: The rapid advancement of generative models has blurred the boundary between synthetic and real imagery, creating an urgent need for reliable deepfake de

Stabilizing On-Policy Distillation for MLLM Reasoning with Global Normalization

arXiv:2606.09091v1 Announce Type: cross Abstract: On-policy distillation (OPD) has recently emerged as an important post-training paradigm. By using a stronger teacher model to provide dense, fine-gra

Still: Amortized KV Cache Compaction in a Single Forward Pass

arXiv:2606.07878v1 Announce Type: new Abstract: The KV cache is the memory bottleneck of long-horizon language model deployment. Practically, a deployable compactor must be lightweight enough to call

Strained Coherence: A Pre-Failure Signal in Coding Agent Execution Trajectories

arXiv:2606.07889v1 Announce Type: cross Abstract: LLM-based coding agents sometimes acknowledge a problem in their own reasoning and then proceed anyway. We call this pattern strained coherence: a saf

Streaming Interventions: Can Video Large Language Models Correct Mistakes as They Occur?

arXiv:2606.09547v1 Announce Type: new Abstract: Learning everyday skills, like cooking a dish, relies increasingly on instructional media such as online videos. This opens the door to the use of video

Stress-testing medical large language models reveals latent safety pathology beyond benchmark accuracy

arXiv:2606.07929v1 Announce Type: new Abstract: Large language models (LLMs) are entering clinical practice based on benchmark accuracy that may fail to detect safety-relevant failure modes. Here we p

Struct-Searcher: Agentic Structural Thinking Advances Multimodal Deep Information Seeking

arXiv:2606.07689v1 Announce Type: new Abstract: Deep research agents have attracted increasing attention for their ability to collect large-scale online information to acquire target knowledge, with r

Structured Neuron Pruning in Deep Neural Networks Using Multi-Armed Bandits

arXiv:2606.07615v1 Announce Type: cross Abstract: Deep neural networks often contain redundant hidden units. Removing individual weights can reduce parameter count, but unstructured sparsity is not al

Subtitle-Aligned Fine-Tuning of Whisper for Swiss German ASR: Benchmark Contamination, Convention Mismatch, and an Honest Baseline at 25.6% WER (13.8% cWER)

arXiv:2606.07608v1 Announce Type: cross Abstract: We present a systematic study of fine-tuning OpenAI's Whisper large-v3 for Swiss German ASR, using 1,367 hours of broadcast speech paired with Standar

Supracompetitive Pricing Under AI Monoculture

arXiv:2601.01279v3 Announce Type: replace-cross Abstract: When competing sellers delegate pricing to a shared AI model, such as a large language model, correlated recommendations combined with perform

SurfDesign: Effective Protein Design on Molecular Surfaces

arXiv:2606.07567v1 Announce Type: cross Abstract: Protein function is largely determined by molecular surface geometry and physicochemical complementarity, yet most protein design methods condition on

SWE-Marathon: Can Agents Autonomously Complete Ultra-Long-Horizon Software Work?

arXiv:2606.07682v1 Announce Type: cross Abstract: AI agents are increasingly expected to complete long-horizon workflows that require sustained progress over hours, millions of tokens, and complex env

Systematic LLM Translation of Legacy Scientific Code to Differentiable Frameworks: Application to a Land Surface Model

arXiv:2606.07681v1 Announce Type: cross Abstract: Differentiable programming offers transformative capabilities for scientific modeling, enabling gradient-based parameter estimation, sensitivity analy

TABVERSE: Benchmarking Cross-Format Table Understanding in LLMs and VLMs

arXiv:2606.09578v1 Announce Type: new Abstract: Large Language Models (LLMs) and Vision-Language Models (VLMs) are increasingly evaluated on table reasoning tasks, but the role of table representation

TAME: A Trustworthy Test-Time Evolution of Agent Memory with Systematic Benchmarking

arXiv:2602.03224v2 Announce Type: replace Abstract: Test-time evolution of agent memory represents a pivotal paradigm for advancing AGI, as it strengthens complex reasoning through experience accumula

TempoBench: Evaluating Temporal Causal Reasoning in Large Language Models

arXiv:2510.27544v2 Announce Type: replace Abstract: Temporal reasoning involves understanding how systems evolve over time through input-driven state transitions. A key aspect is temporal causal reaso

The AI Epistemic Deference Index: A Continuous Measure of Sycophancy

arXiv:2606.07897v1 Announce Type: new Abstract: Current AI models frequently exhibit epistemic sycophancy, endorsing claims to agree with a user. Existing evaluations typically measure this either by

The Injection Paradox: Brand-Level Suppression in Safety-Trained LLM Recommendations via RAG Context Injection

arXiv:2606.09204v1 Announce Type: new Abstract: We present a reproducible failure mode of safety training in RAG-based LLM recommendation -- the Injection Paradox -- in which prompt injections embedde

The Last Visible Pixel: Probing Fine-Scale Perception in Vision-Language Models

arXiv:2606.07861v1 Announce Type: cross Abstract: Recent vision-language models (VLMs) excel at multimodal understanding and reasoning, yet their fine-grained visual perception remains underexplored.

The Montparnasse Algorithm for RNA Design

arXiv:2606.07562v1 Announce Type: cross Abstract: RNA design consists of discovering a nucleotide sequence that optimizes predefined criteria, such as secondary structure. It is useful for synthetic b

The Sample Complexity of Parameter-Free Stochastic Convex Optimization

arXiv:2506.11336v2 Announce Type: replace Abstract: We study the sample complexity of stochastic convex optimization when problem parameters such as the distance to optimality and the Lipschitz consta

TheoremBench: Evaluating LLMs on Theorem Proving in Formal Mathematics

arXiv:2606.09450v1 Announce Type: new Abstract: LLMs have recently achieved strong results on formal proving benchmarks. However, existing evaluations remain heavily concentrated on competition-style

Theoretical Foundations of Continual Learning via Drift-Plus-Penalty

arXiv:2606.08452v1 Announce Type: new Abstract: In many real-world settings, data streams are nonstationary and arrive sequentially, requiring learning systems to adapt continuously without retraining

Thinking-Based Non-Thinking: Solving the Reward Hacking Problem in Training Hybrid Reasoning Models via Reinforcement Learning

arXiv:2601.04805v2 Announce Type: replace Abstract: Large reasoning models (LRMs) have attracted much attention due to their exceptional performance. However, their performance mainly stems from think

Token Sample Complexity of Attention

arXiv:2512.10656v3 Announce Type: replace Abstract: As context windows in large language models continue to expand, it is essential to characterize how attention behaves at extreme sequence lengths. W

Towards Long-Horizon Vessel Trajectory and Destination Forecasting with Reasoning Large Language Models

arXiv:2606.08633v1 Announce Type: new Abstract: Long-horizon maritime trajectory prediction is important for shipping management, logistics planning, and maritime risk analysis, yet month-level foreca

Towards Personalized Bangla Book Recommendation: A Large-Scale Heterogeneous Book Graph Dataset

arXiv:2602.12129v2 Announce Type: replace-cross Abstract: Personalized book recommendation in Bangla literature has been constrained by the lack of structured, large-scale, and publicly available data