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arXiv:2609.01431v1 Announce Type: cross Abstract: Optimal hyperparameter scaling laws describe how the best hyperparameters for large language model (LLM) training change with model and data scale, en

applicationsarxiv-cs-ai

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Model Releases

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

DGX agent

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

model-releasesarxiv-cs-ai

2 Sept 2026

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

model-releasesarxiv-cs-lg

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

Industry

Elon vient de poster un truc simple : presque tout le discours sur l’IA se passe sur X. Ce n’est pas un détail d’audience. C’est le signe qu…

Elon vient de poster un truc simple : presque tout le discours sur l’IA se passe sur X. Ce n’est pas un détail d’audience. C’est le signe que la noosphère est en train de devenir réelle. Teilhard de C

industryelon-musk--x

EM^2Mem: Event-Centric Multimodal Memory for Large Language Models

arXiv:2609.00551v1 Announce Type: cross Abstract: Multimodal memory offers a scalable interface for long-video question answering, but existing methods often retrieve captions, frames, transcripts, su

Embedded Conditional Independence Tests for Large Language Model Generated Text with an Application to German Parliament Speeches

arXiv:2609.00946v1 Announce Type: cross Abstract: Conditional independence tests (CITs) test for conditional dependence between two random objects X and Y given a third random object Z. Existing CITs

EmbodiedSkills: A Unified Framework for Orchestrating, Training, and Deploying VLA Agents

arXiv:2609.01281v1 Announce Type: cross Abstract: Vision-language-action (VLA) models map visual observations and language instructions directly to robot actions, but long-horizon tasks require more t

agentsarxiv-cs-ai

Emotional Labor Strategy Preferences in LLM Personas

arXiv:2609.00310v1 Announce Type: new Abstract: Emotional labor is the effortful management of emotional displays to meet social or professional expectations. Personality traits have been correlated w

researcharxiv-cs-cl

Endoscopic Depth Estimation Based on Deep Learning: A Survey

arXiv:2507.20881v3 Announce Type: replace Abstract: Endoscopic depth estimation is a critical technology for improving the safety and precision of minimally invasive surgery. It has attracted consider

safetyarxiv-cs-cv

Energy-Based Transformers as Predictors of Reading Difficulty

arXiv:2606.23382v2 Announce Type: replace-cross Abstract: Transformer language models have become established tools for modeling human sentence processing, with measures such as surprisal and attentio

Local Ai

Enoki: Efficient Multi-Level Hallucination Detection

arXiv:2609.00581v1 Announce Type: new Abstract: Ensuring factuality remains a critical challenge for deploying LLMs in high-stakes settings. Existing hallucination detectors usually operate at a singl

local-aiarxiv-cs-cl

ES-AHD: An Evolution Strategy Framework for Automatic Heuristic Design

arXiv:2609.00023v1 Announce Type: cross Abstract: In this paper, we introduce ES-AHD, a novel framework that fundamentally integrates Evolution Strategy (ES) into Large Language Model (LLM)-driven Aut

researcharxiv-cs-lg

Escaping Redundant Reasoning: Structure-Aware Search for Inference-Time LLMs

arXiv:2609.00738v1 Announce Type: new Abstract: Inference-time search with large language models (LLMs) often concentrates on a small set of structurally or semantically similar trajectories, leaving

EULER: Exploring Underused Links with Evidence-Checked Return for Multi-Agent Mathematical Discovery

arXiv:2609.00032v1 Announce Type: new Abstract: Mathematical communities work with different objects, invariants, and tools, so transferring a problem across them is expensive and often skipped. We pr

agentsarxiv-cs-ai

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 Second-Order Bias of LLMs Through Epistemic Entitlement

arXiv:2606.17506v2 Announce Type: replace Abstract: Evaluations of social bias in LLMs largely focus on whether models generate or imply biased content. However, as LLMs are increasingly used as judge

safetyarxiv-cs-cl

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-

EvoGS: Modeling Deformation Evolution for Dynamic Gaussian Splatting

arXiv:2609.00994v1 Announce Type: new Abstract: Recent extensions of 3D Gaussian Splatting (3DGS) enable real-time novel view synthesis in dynamic scenes by learning time-conditioned Gaussian deformat

researcharxiv-cs-cv

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

Tutorials

Exact Global MCMC with Denoising Diffusion

arXiv:2609.00279v1 Announce Type: cross Abstract: This work shows that diffusion models learned with standard denoising loss can provide effective global MCMC proposals for complex high-dimensional ta

tutorialsarxiv-cs-lg

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

model-releasesarxiv-cs-lg

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

ExpArt-KG: Artwork Image Description Generation through Iterative Exploration of Knowledge Graphs

arXiv:2609.00629v1 Announce Type: new Abstract: Large Vision-Language Models (LVLMs) achieve strong performance on image-grounded text generation and visual question answering. However, it remains dif

researcharxiv-cs-cl

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

Explicit Interaction Architectures for Dynamical Learning: A Controlled Study of Structural Inductive Bias

arXiv:2606.19101v2 Announce Type: replace-cross Abstract: We investigate a structure-first approach to dynamical learning in which the organization of stateful interactions is prescribed explicitly ra

safetyarxiv-cs-lg

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 Before Committing: Hypothesis-Guided Search for Deep Research Agents

arXiv:2609.01294v1 Announce Type: new Abstract: Deep-research agents answer complex questions by interacting with search and browsing tools, yet they often search along a single evolving trajectory. O

agentsarxiv-cs-cl

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

Exploring Nonlinear Body Oscillations for Natural Quadruped Gaits

arXiv:2609.00539v1 Announce Type: new Abstract: Animals' body morphology shapes the gait patterns they can perform, where mechanical resonance reduces the need for active control. By tuning posture an

researcharxiv-cs-ro

Exploring Sparse Autoencoders in Text-Based Causal Confounding Adjustment

arXiv:2609.01322v1 Announce Type: new Abstract: In many settings, studying causal questions based on text data requires adjusting for confounding information within texts. Yet there is a tradeoff in c

safetyarxiv-cs-cl

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,

Facet-0: A Robotic Foundation Model for Contact-Rich Precise Manipulation

arXiv:2609.01596v1 Announce Type: cross Abstract: Real-world robotic assembly at sub-millimeter tolerances demands spatial precision, compliant interaction, and robustness to contact failures. We pres

safetyarxiv-cs-lg

Fair Minimum Labeling: Efficient Temporal Network Activations for Reachability and Equity

arXiv:2510.03899v3 Announce Type: replace-cross Abstract: Balancing resource efficiency and fairness is critical in networked systems that support modern learning applications. We introduce the Fair M

safetyarxiv-cs-lg

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

Faster Than Flash: Exploiting Attention Sparsity for Efficient Long-Context Decoding

arXiv:2609.00097v1 Announce Type: cross Abstract: The development of long-context Large Language Models (LLMs) is constrained by the memory bandwidth bottleneck and quadratic complexity of the attenti

Fear marketing failed. Here comes the pump.

Jen Zhu (@jenzhuscott) noted on Twitter that “fear marketing failed. Here comes the pump.” Following this, Watcher.Guru shared a new statement: OpenAI CEO Sam Altman declared that AI will become the l

safetygary-marcus--x

Local Ai

Federated Trust for Embodied Robot Capability Marketplaces

arXiv:2609.00404v1 Announce Type: cross Abstract: Robot capability marketplaces, the 'app store for robot skills,' are emerging as the deployment vector for LLM-driven robot fleets. The default cloud-

local-aiarxiv-cs-ro

Tutorials

FedReview: Review and Dispose Poisoned Updates without Validation Datasets or Historic Knowledge

arXiv:2402.16934v2 Announce Type: replace-cross Abstract: Federated learning has emerged as a decentralized approach for training high-performance models without accessing user data. Despite its effec

tutorialsarxiv-cs-ai

Applications

Feed-Forward Multi-view Multi-person Reconstruction with Contrastive Human-Aware 3D Representation

arXiv:2609.00745v1 Announce Type: new Abstract: Multi-view human reconstruction has been extensively studied under simplified settings, yet robust and efficient multi-person reconstruction in unconstr

applicationsarxiv-cs-cv

Feedback-Assisted Trust Propagation over Document Relation Graphs for Retrieval-Augmented Generation

arXiv:2609.00543v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) systems rely on external corpora that may contain outdated, contradictory, noisy, or unreliable documents, introduc

Industry

Fei-Fei Li’s World Labs debuts Atlas, a world model showcase for advanced spatial intelligence

World Labs Inc., the high-profile and well-funded artificial intelligence startup co-founded by the renowned computer vision pioneer Fei-Fei Li, has just dropped Atlas, which promises to be a game-cha

industrysiliconangle

Few-Shot Out of Domain Intent Detection with Covariance Corrected Mahalanobis Distance

arXiv:2609.00961v1 Announce Type: new Abstract: Conversational agents like chatbots and voice assistants are trained to understand and respond to user intents. On encountering an utterance with an int

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

Figures as Programs: Recursive Generation of Editable Scientific Figures

arXiv:2609.01006v1 Announce Type: new Abstract: Scientific methodology figures are essential for communicating complex methods clearly, yet creating them remains labor-intensive and typically requires

agentsarxiv-cs-ai

Finally, a good paper testing if graph memory actually beats flat retrieval for long-term agents. (bookmark this one) Researchers extract ea…

Finally, a good paper testing if graph memory actually beats flat retrieval for long-term agents. (bookmark this one) Researchers extract each conversational turn into typed nodes and attributed edges

researchdair-ai--x