Search: “models”

FlapKAD: A Simulation Dataset of Coupled Wing Kinematics and Aerodynamic Dynamics for Flapping-Wing Aerial Vehicles

model-releasesarxiv-cs-ro

arXiv:2609.38719v1 Announce Type: new Abstract: Experimental investigation and modeling of flapping-wing aerial vehicles are limited by the scarcity of large-scale records that temporally align wing k

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Model Releases

Free Everywhere, Exact on Trees: PPO's Dropped Correction Buys Sample Efficiency Under Aggressive Reuse

DGX agent

arXiv:2609.39634v1 Announce Type: cross Abstract: Common policy improvement methods, including TRPO, PPO, and GRPO, estimate policy improvement under the behavioral policy's state-visitation distribut

model-releasesarxiv-cs-ai

1 Oct 2026

Interpretable but Fragile? Robustness of Concept Bottlenecks under Geometric-Semantic Perturbations

arXiv:2609.38625v1 Announce Type: cross Abstract: Concept Bottleneck Models (CBMs) are designed to provide interpretable intermediate representations, yet how such bottlenecks affect robustness remain

researcharxiv-cs-ai

Learning Chaos Without Seeing Chaos: Extrapolation of Global Dynamics in Autoregressive Transformers

arXiv:2609.38814v1 Announce Type: new Abstract: Autoregressive models are trained to predict a system's behavior one step at a time, and recursive generation allows the learned dynamics to unfold over

LLM Persona Unlearning

arXiv:2609.39882v1 Announce Type: new Abstract: Pre-training equips large language models (LLMs) with a broad repertoire of behavioral patterns associated with roles, styles, values, and goals. Post-t

LongEmo: Towards Emotion Understanding and Reasoning in Long Videos

arXiv:2609.40079v1 Announce Type: cross Abstract: While recent Multimodal Large Language Models (MLLMs) have shown promise in affective computing, their reasoning capabilities are largely confined to

MADBench: Benchmarking the Security of Multi-Agent Debate

arXiv:2609.39146v1 Announce Type: new Abstract: Multi-agent debate (MAD) can improve large language model (LLM) reasoning by allowing multiple agents to exchange and critique their answers to the same

Marginal Response Surface Elicitation for Zero-Label Tabular Learning

arXiv:2609.39639v1 Announce Type: new Abstract: Tabular learning uses structured data to predict target outcomes. Traditionally, this process has relied on labeled data. However, large language models

MetaPersona: Task-Grounded Synthetic Populations from Empirical Social Science

arXiv:2609.38392v1 Announce Type: new Abstract: Personas used to seed LLM social simulations face a cold-start problem: existing methods lack a principled basis for deciding which attributes to includ

OpenCollab: A Multi-Agent Coding Framework with Programmable Collaboration and Controllable Runtime

arXiv:2609.38345v1 Announce Type: cross Abstract: Multi-agent coding systems are designed to tackle complex software engineering tasks through collaboration. However, existing evaluations typically as

Overconfidence and Calibration in Medical VQA: Empirical Findings and Hallucination-Aware Mitigation

arXiv:2604.02543v2 Announce Type: replace Abstract: As vision-language models (VLMs) are increasingly deployed in clinical decision support, more than accuracy is required: knowing when to trust their

researcharxiv-cs-cv

Agents

OverForge: Reasoning Through Strategies and Tactics Helps Cooperative Lifelong Adaptation

arXiv:2609.39727v1 Announce Type: new Abstract: Cooperative language-model agents must coordinate over long horizons and adapt to changing environments and to partners with unfamiliar conventions, yet

agentsarxiv-cs-ai

Overlap, Unique and Conflict: Can LLMs Extract What They Can Recognize?

arXiv:2609.38799v1 Announce Type: new Abstract: Understanding multi-perspective alternative narratives requires identifying how their information agrees, conflicts, or differs across sources. Existing

PCB-MC: Missing Component Analysis in Printed Circuit Boards

arXiv:2609.39427v1 Announce Type: new Abstract: Detecting missing components on printed circuit boards (PCBs) differs fundamentally from conventional object detection, as the model must localize compo

PINNing the pion: conformal deep learning for F_pi(s) and the (g-2)_mu hadronic contribution

arXiv:2609.40008v1 Announce Type: cross Abstract: Extracting the pion electromagnetic form factor F_{pi}(s) through phenomenological curve-fitting models introduces model dependence, unphysical artefa

researcharxiv-cs-lg

PivotOPD: Learning to Recover from Pivotal Mistakes in Multi-Turn Agents

arXiv:2609.40285v1 Announce Type: new Abstract: On-policy distillation (OPD) is a promising approach for training language agents, providing dense teacher supervision on student-generated trajectories

RiboUnmix: Learning Shared Translational Dynamics from Biased and Noisy Ribo-seq Measurements

arXiv:2609.39644v1 Announce Type: new Abstract: Ribosome profiling (Ribo-seq) measures ribosome distributions along mRNAs, but observed occupancy profiles also contain experiment-specific distortions

RoPE at the End of Its Rope? Theory, Diagnosis, and Mitigation of Long-Context Failures

arXiv:2609.39929v1 Announce Type: cross Abstract: Long-context failures of RoPE-based language models can arise from RoPE's intrinsic tradeoff between maintaining stable token preferences and distingu

SCALE: Synthetic Calibration via Agreement Labeling in Embedding Space

arXiv:2609.38705v1 Announce Type: new Abstract: Foundation models for computational pathology are usually evaluated using AUC and accuracy, while calibration is often left untested. This matters becau

researcharxiv-cs-cv

Security Properties of Neural Networks as Decision Problems

arXiv:2609.39768v1 Announce Type: cross Abstract: Certifying a deployed neural network raises decision problems that the verification literature has not classified: whether the model carries a backdoo

SETA: Scaling Environments for Terminal Agents

arXiv:2607.10891v2 Announce Type: replace Abstract: Large language models (LLMs) are rapidly shifting toward agents that solve tasks through diverse interfaces, including web and graphical user interf

Simulator-Refined Diffusion for Radio-Frequency Inverse Design

arXiv:2609.38363v1 Announce Type: cross Abstract: Diffusion models have shown potential in inverse design of printed circuit boards (PCBs), enabling the generation of layouts conditioned on target S-p

researcharxiv-cs-ai

Super-Resolving Unseen Hyperspectral Sensors at Any Scale via Spatial Operators

arXiv:2609.39926v1 Announce Type: new Abstract: Achieving cross-sensor generalization and arbitrary-scale reconstruction with a single model remains challenging in hyperspectral super-resolution (HSR)

Agents

Synthesis Without Training: An Inference-Only Pipeline for Tabular, Temporal, and Relational Synthetic Data

arXiv:2609.38414v1 Announce Type: new Abstract: Synthetic data generation is dominated by the fit-then-sample paradigm: a generative model is trained on a private dataset and then sampled from. Despit

agentsarxiv-cs-lg

Talk2Agent: Benchmarking Voice Interfaces for Text Agents

arXiv:2609.38867v1 Announce Type: new Abstract: Large language model (LLM) computer-use agents are typically evaluated with clean written instructions, despite speech being an increasingly popular int

The Concrete-Arbitrary Gap: Kinship Reasoning in LLMs Is Not Indifferent to Presentation

arXiv:2609.39913v1 Announce Type: new Abstract: We test whether large language models solve formally matched kinship problems equally well when relations are expressed in familiar vocabulary or by exp

Unmerge: Efficient Machine Unlearning via Task Arithmetic

arXiv:2609.38895v1 Announce Type: cross Abstract: Approximate machine unlearning seeks to remove the influence of a forget set from a trained model without full retraining. Existing gradient-based met

When Reasoning Goes Astray: Attention Dynamics of Uncontrolled Reasoning

arXiv:2609.38817v1 Announce Type: new Abstract: Large reasoning models (LRMs) improve performance on complex tasks through extended reasoning, yet the same process can degenerate into redundant verifi

researcharxiv-cs-ai

WorldAuditBench: Interactive 3D World Auditing with Multimodal Agents

arXiv:2609.40325v1 Announce Type: new Abstract: As interactive 3D worlds are increasingly used to study intelligent behavior, it becomes important to develop efficient pipelines for identifying anomal

Agents

AX is the New AEO

arXiv:2609.34951v2 Announce Type: replace Abstract: In 2023, AI models answered from training data and hallucinated when it ran out, and businesses were told to seed that knowledge. Models' training k

agentsarxiv-cs-ai

Beyond Compression: Diagnosing How Post-Training Changes Mathematical Reasoning

arXiv:2609.37066v1 Announce Type: cross Abstract: Post-training is central to mathematical reasoning in modern large language models (LLMs), but endpoint pass@1 alone underidentifies what has changed.

Beyond Pixels: A Vector-to-Graph Framework for Reliable Schematic Auditing

arXiv:2602.11678v2 Announce Type: replace Abstract: Multimodal Large Language Models (MLLMs) have shown remarkable progress in visual understanding, yet they suffer from a critical limitation: structu

Block Sparse Flash Attention

arXiv:2512.07011v2 Announce Type: replace-cross Abstract: Modern large language models increasingly require long contexts for reasoning and multi-document tasks, but attention's quadratic complexity c

Byzantine-Robust Federated Representation Learning

arXiv:2609.36660v1 Announce Type: new Abstract: We study federated learning (FL) with adversarial clients, where the goal is to minimize the average loss of the honest (non-adversarial) clients withou

Character Training for Risk-Averse Agents

arXiv:2609.38093v1 Announce Type: new Abstract: Risk aversion in resources could prevent misaligned AI agents from causing catastrophic harm. Misaligned but risk-averse agents would tend to favor safe

Complexity-Aware Evaluation of LLM Comprehension

arXiv:2609.37405v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used for software engineering tasks that require understanding existing source code, including behavior

Correct Answers, Invalid Traces: What Verifiable Grade-School Math Reveals About Chain-of-Thought Traces

arXiv:2609.38107v1 Announce Type: cross Abstract: Chain-of-thought traces are widely read as records of how models reach their answers, informing debugging, agent auditing, and claims about reasoning.

CoVLM-Bench: A Real-World Benchmark for Cooperative Driving Question Answering and Planning

arXiv:2609.35823v1 Announce Type: new Abstract: Vision-language models (VLMs) have made substantial progress in autonomous driving, but their success has primarily been studied in ego-centric scenes.

CRJudgeBench: Can AI Detect Plausible but Invalid Code Reviews?

arXiv:2609.37216v1 Announce Type: cross Abstract: Large language models can generate plausible code-review comments, but such comments may contain technically incorrect claims that mislead developers.

EASE: Behavior-Adaptive Skill Curation for Self-Evolving Agents

arXiv:2609.36746v1 Announce Type: new Abstract: Agent skills provide a lightweight mechanism for self-evolving agents to accumulate reusable procedural knowledge without updating model parameters. How

Encoder-Sharing Hierarchical Federated Multi-Task Learning for VANETs

arXiv:2609.36157v1 Announce Type: cross Abstract: Most federated learning frameworks for vehicular ad hoc networks assume that all vehicles collaboratively train a single model for a common task. This

Engineering Simplicity: Simple Mechanism Interfaces Steer LLM Agents

arXiv:2609.36365v1 Announce Type: new Abstract: Can interaction formats and textual scaffolds help large language model (LLM) agents make better decisions, and do better decisions come with better exp

Exploring In-Context Learning for Handwritten Text Recognition

arXiv:2609.37195v1 Announce Type: new Abstract: Handwritten Text Recognition (HTR) systems have become an indispensable tool for the digitization of historical documents. Not only do they cut down tim

Gondola: Grounded Vision Language Planning for Robotic Manipulation

arXiv:2506.11261v2 Announce Type: replace-cross Abstract: Vision-language-action (VLA) models have shown promising progress in robotic manipulation. However, directly mapping visual observations and l

Homo-RAG: Homology-Guided Retrieval-Augmented Generation for Cross-Species Gene Function Prediction

arXiv:2608.25466v2 Announce Type: replace-cross Abstract: The functional annotation of genes in non-model organisms remains a significant challenge in computational biology, with 20-70% of sequenced g

Inducing Process Supervision from Outcome-Only Reinforcement Learning

arXiv:2609.36641v1 Announce Type: cross Abstract: Process reward models (PRMs) have become a key component for LLMs, as their step-level feedback supports both post-training and test-time reasoning. H

Learn Now, Use Next, Trust Later: Prequential Test-Time Learning for LLM Agents

arXiv:2609.35911v1 Announce Type: cross Abstract: Adapting large language model agents during deployment requires not only retaining past experience, but also turning new observations into timely guid

Tutorials

Learning the Structure of Triangular Transport Maps

arXiv:2609.37122v1 Announce Type: new Abstract: Triangular transport maps provide a flexible approach to sampling-based probabilistic modeling, including density estimation, generative modeling, and B

tutorialsarxiv-cs-lg