Search: “model-releases”

CoLT-Drive: Counterfactual Long-Tail Benchmarking and Knowledge-Preserving Adaptation for Driving Affordance Prediction

arXiv:2609.00242v1 Announce Type: cross Abstract: Long-tail autonomous driving failures are often framed as rare-object recognition errors. We argue that this view is incomplete: the decision-critical

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Model Releases

CoMMET: A Psychologically Grounded Benchmark for Evaluating Theory of Mind in Multimodal LLMs

DGX agent

arXiv:2603.11915v2 Announce Type: replace Abstract: Theory of Mind (ToM)-the ability to reason about the mental states of oneself and others-is a cornerstone of human social intelligence. As Multimoda

model-releasesarxiv-cs-cl

2 Sept 2026

CompanionSim: Synthetic Data for Evaluating Anthropomorphism in Human-AI Relationships

arXiv:2609.00250v1 Announce Type: cross Abstract: Many people now see AI systems as not just productivity tools but as social companions. Researchers are eager to study the consequences of AI companio

Compositional Machine Design as Program Synthesis with LLMs

arXiv:2510.14980v3 Announce Type: replace Abstract: Large language models (LLMs) have shown strong abilities in writing and revising programs, yet many program-synthesis benchmarks still evaluate prog

Compressing AI Traffic: Standardized Neural Network Coding of Visual-Token Representations in Split Vision-Language Inference

arXiv:2609.01200v1 Announce Type: new Abstract: When the visual encoder and the language decoder of a vision-language model (VLM) run on different compute nodes, the intermediate visual-token embeddin

Computational Humor with Multimodal LLMs: Methods, Datasets, Evaluation, and Challenges

arXiv:2607.19011v2 Announce Type: replace-cross Abstract: Multimodal humor in memes, cartoons, and comics remains difficult for AI systems because intended meaning depends on non-literal mechanisms, s

Conditional Flow Matching for Cross-Field MRI Harmonisation

arXiv:2609.00960v1 Announce Type: new Abstract: Magnetic resonance images of the same subject look markedly different across field strengths, which complicates the comparison and pooling of data acros

Context Window Failures in Relational Foundation Models

arXiv:2609.00460v1 Announce Type: new Abstract: Recent Relational Deep Learning architectures have been proposed as foundation models for multi-table relational data, yet they impose constrained neigh

ContextPipe: Database-Inspired Context Assembly for Long-Horizon Agents

arXiv:2609.00749v1 Announce Type: new Abstract: Long-horizon large language model (LLM) agents require context assembly: the runtime must decide what to include in each prompt, in what order, and when

Controllable Image Captioning with Prompt-Conditioned Scene Rewards

model-releasesarxiv-cs-cl

arXiv:2609.00709v1 Announce Type: cross Abstract: Large Vision-Language Models produce fluent image descriptions but offer limited semantic control: users cannot reliably specify whether captions shou

CopyShield: A Cross-Level Benchmark of Copyright Defenses in LLMs

arXiv:2609.01161v1 Announce Type: new Abstract: Large language models can reproduce memorized text verbatim, yet copyright defenses are usually evaluated under incompatible protocols. We introduce Cop

CordisBench: Can Language Models Reason About Component Lifecycles in Dynamic Agent Harnesses?

arXiv:2609.01600v1 Announce Type: cross Abstract: Dynamic agent harnesses let language models change the software that shapes their own execution. This flexibility brings a new reasoning burden: a loc

Counterfactual Closing-Acceleration Risk: An Anticipatory Surrogate Safety Measure for the Blind Region of Car-Following

model-releasesarxiv-cs-ro

arXiv:2609.00370v1 Announce Type: cross Abstract: Surrogate safety measures allow road-safety assessment from trajectory data in which crashes are absent, yet the dominant proximity measures - time-to

CRAD: Class-wise Reliability-Aware Distillation for Decentralized Heterogeneous Federated Learning

arXiv:2609.00446v1 Announce Type: cross Abstract: Conventional federated learning (FL) relies on parameter averaging, which forces clients to be doubly homogeneous: it demands an identical architectur

DAGGER: Distractor-Aware Graph Generation for Executable Reasoning in Math Problems

model-releasesarxiv-cs-cl

arXiv:2601.06853v3 Announce Type: replace Abstract: Chain-of-Thought (CoT) prompting is widely adopted for mathematical problem solving, including in low-resource languages, yet its behavior under irr

Data-Driven Persona-Conditioned Agents for A/B Test Simulation

arXiv:2609.01038v1 Announce Type: new Abstract: A/B testing is the gold standard for evaluating product changes, but each experiment requires real user traffic, engineering effort, and weeks of measur

Defense-as-Skill: Evolving Runtime Guard Skill for Skill-Augmented Agents

arXiv:2609.01487v1 Announce Type: cross Abstract: Skill-augmented agents load reusable skills as persistent runtime context, improving task performance but also giving malicious skills a durable chann

Dependency-Aware Chain-of-Thought Compression for Financial Reasoning

arXiv:2609.00413v1 Announce Type: new Abstract: Chain of thought prompting improves complex reasoning, but its long intermediate traces create substantial inference cost and hinder practical deploymen

DeSyR: A Decoupled Symbolic Recovery Framework with PINN-Guided Structure Search and Physics-Informed Coefficient Refinement

arXiv:2609.00530v1 Announce Type: new Abstract: Recovering compact explicit solutions from neural approximations is challenging when imperfect teacher data guide symbolic topology search and coefficie

Disclosure-Gated User Simulation for Companion-Agent Evaluation

arXiv:2609.00982v1 Announce Type: cross Abstract: Using a large language model to play the user is now standard in scalable evaluation. It has a repeatedly diagnosed failure: the simulated user is exc

Discrete-Time MDP Modeling for Multi-Item Capacitated Lot Sizing with Stochastic Demand Timing

arXiv:2609.00004v1 Announce Type: new Abstract: This paper studies a finite-horizon multi-item capacitated lot-sizing problem in which demand quantities are deterministic, while demand-arrival periods

DISTAL: Distillation and Self-Supervised Pretraining for Structure-Agnostic Materials Property Prediction

arXiv:2609.00059v1 Announce Type: cross Abstract: Materials property prediction remains difficult in low-data settings, where many target properties are supported by only a limited number of labeled s

Do General NLP Embeddings Capture Ontological Reasoning?

arXiv:2609.00177v1 Announce Type: cross Abstract: General-purpose NLP embedding models perform well on linguistic tasks, but their ability to capture symbolic ontological structure remains unclear. We

Do Multimodal LLMs See Before They Read? Diagnosing Contextual Sycophancy

arXiv:2609.00067v1 Announce Type: cross Abstract: External text can override conflicting image evidence in multimodal large language models, a failure we call multimodal contextual sycophancy. We intr

Do Satellites See Commuters? A Critical Benchmark of Vision Foundation Models

arXiv:2609.00661v1 Announce Type: new Abstract: Satellite foundation models offer a globally available alternative to census data for commuting origin-destination (OD) generation, yet no study has sys

Does Imitation Learning Preserve Temporal Robustness in Dexterous Manipulation? An Expert-Learner Comparison Across Task Execution Speeds

arXiv:2609.01453v1 Announce Type: cross Abstract: Dexterous manipulation policies learned by imitation are typically evaluated for robustness to variation in scenes, objects, or instructions, but thei

Don't Let the Model Write the YAML: Deterministic, Minimal-Diff GitOps Remediation from LLM-Proposed Field Changes

arXiv:2609.00227v1 Announce Type: cross Abstract: LLM agents increasingly diagnose incidents and propose remediations. In a GitOps workflow, applying a fix means editing a version-controlled config fi

Dr. Claw: An AI Scientist Workspace for Vibe Research

arXiv:2609.00365v1 Announce Type: new Abstract: Command-line coding agents (e.g., Claude Code, Gemini CLI) can already read and write files and sustain long sessions, yet end-to-end research still fra

DramaChain Bench: An End-to-End Benchmark for Short-Drama Generation

arXiv:2609.00646v1 Announce Type: new Abstract: Commercial short-drama production follows a multi-stage chain: script, storyboard, keyframe imagery, shot-level video, and the finished short drama. Mos

Drift-Aware LLM Routing with Sparse Contexts and Shared Budgets

arXiv:2609.00662v1 Announce Type: new Abstract: A multi-model language service must route each request while preserving workload-level budgets for compute, latency, memory, or monetary cost. Two featu

DSG: Dynamic 3D Scene Graph Construction for Embodied Agents in Changing Indoor Environments

model-releasesarxiv-cs-ro

arXiv:2609.00619v1 Announce Type: new Abstract: In indoor environments, object positions frequently change due to human activities or embodied-agent interactions, causing previously constructed scene

Dual Process Motion Planning

arXiv:2609.01260v1 Announce Type: new Abstract: Robotic systems are deeply embedded in both industry and everyday life, where they are expected to act with speed, precision, and reliability. Classical

Dyn-3D: Unveiling and Resolving Ego-Motion Ambiguity in Vision-Language Models

arXiv:2609.01059v1 Announce Type: new Abstract: As Vision-Language Models (VLMs) tackle dynamic 3D spatial reasoning, ego-motion perception becomes essential to resolve monocular scale ambiguity. Howe

DynaNDE: Dynamic Near-Data Expert Scheduling for Batched MoE Inference

arXiv:2609.00407v1 Announce Type: cross Abstract: Mixture-of-Experts (MoE) models enable efficient scaling of large language model (LLM) inference but suffer from substantial data-movement overhead wh

EarthLD: Towards Unified Open-World Landslide Understanding via Vision-Language Guided Diffusion Models

arXiv:2609.00712v1 Announce Type: new Abstract: Landslides are widespread geological hazards, yet their automated detection and mapping in remote sensing imagery remain challenging because of their ir

Edge-Girth as a Structural Edge Feature for Graph Neural Networks

arXiv:2609.01441v1 Announce Type: new Abstract: Graph neural networks (GNN) based on message passing are provably no more powerful than the one-dimensional Weisfeiler--Leman colour-refinement test (1-

EdiTikZ: Scientific Figure Editing from Revision Trajectories

arXiv:2609.01409v1 Announce Type: new Abstract: Vision-language models (VLMs) have shown strong performance in generating scientific figures from text or images. However, producing publication-ready f

EDRAC: Benchmarking Arabic Dialect Reading Comprehension

arXiv:2609.01113v1 Announce Type: cross Abstract: Dialectal Arabic (DA) remains under-resourced compared to Modern Standard Arabic (MSA), particularly for machine reading comprehension (MRC) and quest

Efficient and Robust Absolute Pose Estimation via Gravity-Prior-Driven Transformation Decoupling and Pose Refinement

arXiv:2609.00713v1 Announce Type: new Abstract: Estimation of the absolute pose of an object is an essential task for various robotic applications. Recently, incorporating gravity direction as prior i

Efficient Learning of Balanced Signed Graphs via Sparse Linear Programming

arXiv:2506.01826v2 Announce Type: replace Abstract: Signed graphs are equipped with both positive and negative edge weights, encoding pairwise correlations as well as anti-correlations in data. A bala

Efficient SWE Agent Benchmarking via Trajectory-Aware Evaluation

arXiv:2609.01603v1 Announce Type: cross Abstract: Evaluating software engineering agents on realistic benchmarks is costly, since each task may require multi-step code exploration, modification, and t

EGT-KG: Evidence-Grounded Typed KG Retrieval for Practical Scientific QA with Small Language Models

arXiv:2609.00479v1 Announce Type: new Abstract: For emerging scientific research domains, local Small Language Models (SLMs) are becoming more attractive, as they offer stronger privacy control and mo

Elite-Weighted Supervised Fine-tuning for Goal-Directed Molecular Optimization

arXiv:2609.00189v1 Announce Type: new Abstract: Goal-directed optimization is essential for steering molecular generators to propose candidates with desired properties. However, it is often implemente

Evaluating Multimodal LLMs as Generalist Vision-Language-Action Agents for Drone Control: Commanding, Approaching, Tracking and Searching

arXiv:2609.01404v1 Announce Type: cross Abstract: Multimodal Large Language Models (MLLMs) are strong perceivers of images and video. We ask how far that reach extends into acting: dropping an MLLM di

Evaluating Style-Personalized Text Generation: Challenges and Directions

model-releasesarxiv-cs-cl

arXiv:2508.06374v4 Announce Type: replace Abstract: With the surge of large language models (LLMs) and their ability to produce customized output, style-personalized text generation--'write like me'--

EvoFlint: An Evolutionary Atlas of Multi-Turn LLM Vulnerabilities

arXiv:2609.00487v1 Announce Type: cross Abstract: Frontier language models that refuse harmful single-turn prompts often comply when the same intent is reached gradually over many turns, making multi-

EvoSCM: Scientific Belief Revision Through Causal Model Evolution and Experimentation

arXiv:2609.01526v1 Announce Type: new Abstract: Scientific agents must learn not only how to reason, but also what to believe. However, existing LLM agents typically express scientific hypotheses in f

Exact Risk-Complexity Laws for Projective Boundaries in Scenario Optimization and Distribution-Free Certification

arXiv:2609.01355v1 Announce Type: cross Abstract: Scenario optimization, conformal prediction, and related distribution-free certification methods use finite samples to construct decisions or predicti