Search: “models”

Probability Distributions Computed by Autoregressive Transformers

arXiv:2510.27118v4 Announce Type: replace Abstract: Most expressivity results for transformers treat them as language recognizers -- devices that accept or reject strings -- rather than as they are us

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Proper Scoring Rules for Agentic Uncertainty Quantification

DGX agent

arXiv:2605.24756v1 Announce Type: new Abstract: Language-model agents increasingly emit uncertainty signals throughout a trajectory, but existing agentic UQ evaluations often conflate ranking usefulne

agentsarxiv-cs-ai

26 May 2026

Psychometric Item Validation Using Virtual Respondents with Trait-Response Mediators

arXiv:2507.05890v4 Announce Type: replace-cross Abstract: As psychometric surveys are increasingly used to assess the traits of large language models (LLMs), the need for scalable survey item generati

Quantifying Empirical Compute-Supervision Tradeoffs in RLVR

arXiv:2605.25252v1 Announce Type: cross Abstract: Reinforcement learning with verifiable rewards (RLVR) has become a standard paradigm for post-training language models, but in practice, verifiers are

Quantitative Evaluation of the Severity of Posttraumatic Stress Disorder through Transfer Learning from Specific Phobia Data

arXiv:2605.25933v1 Announce Type: cross Abstract: Posttraumatic stress disorder (PTSD) is a prevalent and debilitating mental health condition with significant personal and societal impacts. Current c

RecGOAT: Graph Optimal Adaptive Transport for LLM-Enhanced Multimodal Recommendation with Dual Semantic Alignment

arXiv:2602.00682v2 Announce Type: replace-cross Abstract: Integrating large language model (LLM) representations into multimodal recommendation has shown promise, yet a fundamental challenge remains l

Referential Security as a New Paradigm for AI Evaluations

arXiv:2605.25673v1 Announce Type: cross Abstract: Security evaluations inherently depend on stable identifiers. Any finding, audit, or regulatory decision must remain attached to the specific artifact

Representation-Guided Discrete Molecular Graph Retrosynthesis

arXiv:2605.24428v1 Announce Type: new Abstract: Stochastic process-based molecular graph generators have become the state of the art for template-free single-step retrosynthesis. However, these models

Local Ai

Retrieval-Augmented Detection of Potentially Abusive Clauses in Chilean Terms of Service

arXiv:2605.26019v1 Announce Type: cross Abstract: Online Terms of Service often function as contracts of adhesion, creating asymmetries that may expose consumers to potentially abusive clauses. In Chi

local-aiarxiv-cs-ai

Routing by Analogy: kNN-Augmented Expert Assignment for Mixture-of-Experts

arXiv:2601.02144v2 Announce Type: replace-cross Abstract: Mixture-of-Experts (MoE) architectures scale large language models efficiently by employing a parametric ``router'' to dispatch tokens to a sp

Safety-Critical Whole-Body Control for Humanoid Robots via Input-to-State Safe Control Barrier Functions

arXiv:2605.25546v1 Announce Type: new Abstract: Safety-critical control is essential for humanoid robots operating in complex human-centered environments, where physical safety constraints such as joi

safetyarxiv-cs-ro

Scaling Natural-Language Graph-Based Test Time Compute for Automated Theorem Proving

arXiv:2503.11657v3 Announce Type: replace Abstract: Large language models have demonstrated remarkable capabilities in natural language processing tasks requiring multi-step logical reasoning capabili

Agents

Security of OpenClaw Agents: Fundamentals, Attacks, and Countermeasures

arXiv:2605.25435v1 Announce Type: new Abstract: The rapid evolution of large language model (LLM)-driven autonomous agents has given rise to OpenClaw, a new class of open-source agent frameworks that

agentsarxiv-cs-ai

Selective Latent Thinking: Adaptive Compression of LLM Reasoning Chains

arXiv:2605.25745v1 Announce Type: new Abstract: Explicit chain-of-thought (CoT) reasoning substantially improves the reasoning ability of large language models (LLMs), but incurs high inference cost d

safetyarxiv-cs-cl

Some Robustness Properties of Label Cleaning

arXiv:2509.11379v3 Announce Type: replace-cross Abstract: We demonstrate that learning procedures that rely on aggregated labels, e.g., label information distilled from noisy responses, enjoy robustne

SPACE: Unifying Symmetric and Asymmetric Routing Problems for Generalist Neural Solver

arXiv:2605.24484v1 Announce Type: new Abstract: Generalist neural routing solvers have shown great potential in solving diverse vehicle routing problems (VRPs) with a unified model. However, existing

applicationsarxiv-cs-ai

Local Ai

Spatio-temporal, multi-field deep learning of shock propagation in meso-structured media

arXiv:2509.16139v5 Announce Type: replace Abstract: Predicting the extreme hydrodynamic response of porous and architected lattice materials is a fundamental challenge in high energy density physics,

local-aiarxiv-cs-lg

SpecAlign: A Semantic Alignment Framework for SystemVerilog Assertion Generation

arXiv:2605.25181v1 Announce Type: new Abstract: Existing Large Language Model (LLM) approaches to SystemVerilog Assertion (SVA) generation primarily focus on syntactic validity and formal verification

STaT: Resolving Shape Distortion in Non-Stationary Time Series via Tri-Modal Synergy

arXiv:2605.25943v1 Announce Type: new Abstract: Recent research in time series forecasting frequently investigates the integration of textual and visual modalities with numerical models to better navi

safetyarxiv-cs-lg

Step-TP: A Grounded, Step-Level Dataset with Chain-of-Thought Reasoning for LLM-Guided Tensor Program Optimization

arXiv:2605.25954v1 Announce Type: cross Abstract: Despite the strong reasoning capabilities of large language models (LLMs), optimizing the execution efficiency of tensor programs remains challenging

Strat-Reasoner: Reinforcing Strategic Reasoning of LLMs in Multi-Agent Games

arXiv:2605.04906v2 Announce Type: replace Abstract: While Large Language Models (LLMs) excel in certain reasoning tasks, they struggle in multi-agent games where the final outcome depends on the joint

StrTransformer: Source-Wise Structured Transformers for Unsupervised Blind Source Recovery

arXiv:2605.25648v1 Announce Type: cross Abstract: This paper proposes StrTransformer, a source-wise structured Transformer framework for blind source recovery and branch-wise latent modeling. Instead

applicationsarxiv-cs-lg

Sum of Costs Diffusion with Dynamic Guidance for Motion Planning

arXiv:2605.24690v1 Announce Type: cross Abstract: The motion planning problem for robotic manipulation can be addressed through classical or deep learning approaches. Existing methods face significant

The Multilingual Curse at the Retrieval Layer: Evidence from Amharic

arXiv:2605.24556v1 Announce Type: cross Abstract: Multilingual retrieval increasingly underpins cross-lingual question answering and retrieval-augmented generation. Strong zero-shot scores on multilin

The Quantization Benefits of Residual-Free Transformers

arXiv:2605.25880v1 Announce Type: new Abstract: Large-scale transformer training and deployment are increasingly constrained by the transfer of activations, gradients, and optimizer states across acce

Tutorials

Today's Training Data episode takes us BTS on the infrastructure challenges required to do large RL runs at scale, featuring @ellev3n11 (Com…

Today's Training Data episode takes us BTS on the infrastructure challenges required to do large RL runs at scale, featuring @ellev3n11 (Composer Lead at @cursor_ai) and @dzhulgakov (Co-Founder at @Fi

tutorialssonya-huang--x

TorchLean: Formalizing Neural Networks in Lean

arXiv:2602.22631v2 Announce Type: replace-cross Abstract: Neural networks are increasingly deployed in scientific, safety critical, and mission critical pipelines, yet verification and analysis are of

safetyarxiv-cs-lg

Towards Long-Horizon Interpretability: Efficient and Faithful Multi-Token Attribution for Reasoning LLMs

arXiv:2602.01914v2 Announce Type: replace Abstract: Token attribution methods provide intuitive explanations for language model outputs by identifying causally important input tokens. However, as mode

Towards trustworthy agentic AI: a comprehensive survey of safety, robustness, privacy, and system security

arXiv:2605.23989v1 Announce Type: new Abstract: Agentic AI systems -- Large Language Models (LLMs) augmented with planning, tool use, memory, and long-horizon interactions -- can execute complex tasks

Trait-Aware Policy Optimization for Autoregressive Multi-Trait Essay Scoring

arXiv:2605.25731v1 Announce Type: new Abstract: Multi-trait essay scoring aims to provide fine-grained evaluation of writing quality across multiple dimensions. However, how to effectively post-train

safetyarxiv-cs-cl

Understanding, Accelerating, and Improving MeanFlow Training

arXiv:2511.19065v2 Announce Type: replace-cross Abstract: MeanFlow promises high-quality generative modeling in few steps, by jointly learning instantaneous and average velocity fields. Yet, the under

Variable Clustering via Distributionally Robust Nodewise Regression

arXiv:2212.07944v3 Announce Type: replace Abstract: We study a multi-factor block model for variable clustering and connect it to regularized subspace clustering through a distributionally robust vers

Voting with the Graph: Stable RLAIF via Topological Consistency Maximization

arXiv:2510.15514v3 Announce Type: replace Abstract: Reinforcement Learning from AI Feedback (RLAIF) relies on LLM judges as preference measurement instruments, yet these instruments are fundamentally

What Happens Next? Anticipating Future Motion by Generating Point Trajectories

arXiv:2509.21592v2 Announce Type: replace-cross Abstract: We consider the problem of forecasting motion from a single image, i.e., predicting how objects in the world are likely to move, without the a

applicationsarxiv-cs-ai

What Questions Should Robots Be Able to Answer? A Dataset of User Questions for Explainable Robotics

arXiv:2510.16435v2 Announce Type: replace-cross Abstract: With the growing use of large language models and conversational interfaces in human-robot interaction, robots' ability to answer user questio

When Does Multi-Agent RL Improve LLM Workflows? Workflow, Scale, and Policy-Sharing Tradeoffs

arXiv:2605.24202v1 Announce Type: new Abstract: Multi-agent LLM workflows route inference through specialized roles to lift end-task accuracy, but jointly training those roles with reinforcement learn

Agents

You can’t build an autonomous agent on a static RAG pipeline. Because goals mutate dynamically, agents require an advanced knowledge infrast…

You can’t build an autonomous agent on a static RAG pipeline. Because goals mutate dynamically, agents require an advanced knowledge infrastructure, rather than forcing the model to hunt through a raw

agentspinecone--x

4DThinker: Thinking with 4D Imagery for Dynamic Spatial Understanding

arXiv:2605.05997v2 Announce Type: replace Abstract: Dynamic spatial reasoning from monocular video is essential for bridging visual intelligence and the physical world, yet remains challenging for vis

safetyarxiv-cs-cv

A Simple Plug-in for Improving Eviction-Based KV Cache Compression

arXiv:2605.23258v1 Announce Type: new Abstract: KV cache growth is a major bottleneck for long-context inference in large language models. Existing methods are often dominated by binary eviction or re

Tutorials

Accelerating Divisible Load Processing Through Machine Learning: A Practical Framework for Large-Scale Workloads

arXiv:2605.23247v1 Announce Type: new Abstract: In this paper, we introduce the first machine learning framework for predicting optimal processing times in Single-Level Tree Network (SLTN) architectur

tutorialsarxiv-cs-lg

Amortized Simulation-Based Inference in Generalized Bayes via Neural Posterior Estimation

arXiv:2601.22367v2 Announce Type: replace-cross Abstract: Generalized Bayesian Inference (GBI) tempers a loss with a temperature eta > 0 to mitigate overconfidence and improve robustness under model m

ARES: Automated Rubric Synthesis for Scalable LLM Reinforcement Learning

arXiv:2605.23454v1 Announce Type: new Abstract: Rubric-based rewards offer a promising way to extend reinforcement learning (RL) for large language models beyond tasks with automatically verifiable an

applicationsarxiv-cs-cl

Automatic Construction of Clinical Scoring Systems with LLM Agents

arXiv:2601.22324v2 Announce Type: replace Abstract: Modern clinical practice relies on evidence-based guidelines implemented as compact scoring systems composed of a small number of interpretable deci

Beyond Binary Edits Robust Multimodal Knowledge Editing with Adversarial Subspace Alignment

arXiv:2605.23780v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) need efficient mechanisms to update knowledge without degrading existing capabilities. While intrinsic multimod

BVI-RLV: A Fully Registered Dataset for Low-Light Video Enhancement

arXiv:2407.03535v3 Announce Type: replace Abstract: Low-light videos often exhibit spatiotemporally incoherent noise, compromising visibility and degrading performance in computer vision applications.

applicationsarxiv-cs-cv

CP or DP? Why Not Both: A Case Study in the Partial Shop Scheduling Problem

arXiv:2605.23569v1 Announce Type: new Abstract: Dynamic Programming (DP) and Constraint Programming (CP) are well-established paradigms for solving combinatorial optimization problems. Usually, these

applicationsarxiv-cs-ai

Cross-attention-based bipartite graph neural network for coupled nodal and elemental field prediction in large-deformation sheet material forming

arXiv:2605.22845v1 Announce Type: cross Abstract: Finite element simulations of large-deformation sheet material forming involve node-element coupling between nodal kinematics and element-level deform

Dirichlet-Based Monte Carlo Dropout for Uncertainty Estimation in Neural Networks

arXiv:2605.23635v1 Announce Type: cross Abstract: Traditional neural networks provide deterministic predictions without inherent uncertainty estimates. While Bayesian Neural Networks (BNNs) offer a pr