Search: “model-releases”

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

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Model Releases

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

DGX agent

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

model-releasesarxiv-cs-ai

2 Sept 2026

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 count out Gemini just yet. Feels like a new era of model releases. Models are so powerful that they now come with cyber variants. Love…

Don't count out Gemini just yet. Feels like a new era of model releases. Models are so powerful that they now come with cyber variants. Love the pricing on Gemini 3.8 Flash. Performance not bad. Gemin

model-releasesdair-ai--x

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

ExBind: A Controlled Diagnostic Benchmark for Visual-to-Executable Correspondence

arXiv:2609.01344v1 Announce Type: new Abstract: Multimodal coding and editing systems must map a visible or semantic referent to the exact executable object that can be edited. A wrong reference may s

Expert-like Bone Ultrasound Segmentation through Expert-in-the-loop Mask-conditioned Progressive Learning

arXiv:2609.00473v1 Announce Type: cross Abstract: Manual annotation remains a major bottleneck in ultrasound (US) bone segmentation, where experts typically iteratively refine rough brush masks rather

Exploiting Stability-Plasticity Asymmetry in Pretrained Detectors for Incremental Object Detection

arXiv:2504.10214v2 Announce Type: replace Abstract: Pretrained model-based incremental object detection (PTMIOD) leverages the rich detection priors of pretrained detectors to learn new categories inc

Explore More, Drift Less: Outcome-Only Reinforcement Learning Can Suffice for Long-Horizon Interactive Agents

arXiv:2609.01245v1 Announce Type: cross Abstract: Reinforcement learning is a natural way to post-train LLM agents for long-horizon interactive tasks judged only by end-of-task verification, yet a sha

Exploring Collaboration between a language and a non-language agent

arXiv:2609.00474v1 Announce Type: cross Abstract: LLMs are increasingly deployed as orchestrators that coordinate specialized subagents to solve complex tasks through natural language. However, in man

ExtractBench is now live on @Kaggle. It tests schema-guided document extraction on the documents most likely to break downstream agents and …

model-releasesjerry-liu--x

ExtractBench is now live on @Kaggle. It tests schema-guided document extraction on the documents most likely to break downstream agents and workflows, including long record lists, noisy scans, handwri

Fable 5.1 didn't come with document OCR benchmarks, so we benchmarked it on ParseBench: a comprehensive parsing benchmark that's comprised o…

model-releasesjerry-liu--x

Fable 5.1 didn't come with document OCR benchmarks, so we benchmarked it on ParseBench: a comprehensive parsing benchmark that's comprised of 2k+ real-world documents across finance, legal, insurance,

FaST: Feature-aware Sampling and Tuning for Personalized Preference Alignment with Limited Data

model-releasesarxiv-cs-cl

arXiv:2508.04698v2 Announce Type: replace Abstract: LLM-powered conversational assistants are often deployed in a one-size-fits-all manner, which fails to accommodate individual user preferences. Rece

Fi-ImageNet-1k: An OOD Benchmark From the Inside of the ImageNet-1k Validation Set

arXiv:2609.01027v1 Announce Type: new Abstract: Out-of-distribution (OOD) detection predicts whether a test image belongs to none of the predefined classes. To evaluate this task, benchmarks need imag

FinLifeBench: Exhaustive Life-Event History and Financial-State Reconstruction from Longitudinal Banking Dialogue

arXiv:2609.01198v1 Announce Type: new Abstract: Repeated banking interactions require assistants to maintain complete, current, and traceable customer records as life changes emerge incidentally in ro

First local-LLM tuning attempt: Qwen3.8-27B true Q4_K_M at 13.2 tok/s near 50-61K context on RTX 5080 16GB

model-releasesr-localllama

This was my first serious attempt at tuning a local LLM. I started because Qwen3.8-27B IQ3 was fast on my RTX 5080 but the coding quality disappointed me, and the Q4 profiles I tried in LM Studio were

Fleets Need a Context Plane: Rethinking Cooperative Perception for Autonomous Drones

model-releasesarxiv-cs-ro

arXiv:2609.00659v1 Announce Type: new Abstract: Cooperative perception allows a drone fleet to combine observations from multiple viewpoints. However, existing systems typically fix their feature-shar

FlexP-SFT: A Flexible Aggregation-Free Framework for On-Device Personalized Split Federated Fine-Tuning of LLMs

arXiv:2508.10349v2 Announce Type: replace-cross Abstract: To fine-tune large language models (LLMs) over private data, federated learning (FL) has emerged as a promising paradigm. However, the prohibi