Search: “benchmark”

arXiv:2609.03844v1 Announce Type: cross Abstract: We introduce Stateless Bernoulli Watermarking (SBW), a new statistical watermark for Large Language Models that determines green list membership throu

hardwarearxiv-cs-cl

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Genetic Algorithms for Tractable Bayesian Network Fusion via Pre-Fusion Edge Pruning

DGX agent

arXiv:2609.03724v1 Announce Type: cross Abstract: Bayesian Network (BN) fusion combines multiple input networks into a single structure, balancing dependency preservation with computational tractabili

applicationsarxiv-cs-lg

4 Sept 2026

Gradients Know What Outcomes Don't: Unlocking Reinforcement Learning for LLM Reasoning with Gradient-Aligned Rewards

arXiv:2609.03342v1 Announce Type: new Abstract: Reinforcement learning from verifiable rewards (RLVR) drives chain-of-thought reasoning in large language models, yet its binary outcome reward cannot d

safetyarxiv-cs-lg

GrowPage: On-Demand KV Budgeting for Efficient LLM Reasoning Serving

arXiv:2609.03494v1 Announce Type: new Abstract: Long-output reasoning has made the key--value (KV) cache a critical memory bottleneck for efficient LLM serving. Existing KV compression methods usually

researcharxiv-cs-ai

Hadronic Mono-Z Dark Matter Sensitivity with Flow Matching on CMS Open Data

arXiv:2609.02923v1 Announce Type: cross Abstract: We present a projected sensitivity study for hadronic mono-Z dark-matter production using CMS Run~2015D HTMHT open data corresponding to 2.256382381~i

safetyarxiv-cs-lg

Headroom-Drift Replay: A Primitive for Principled Replay Control in GRPO

arXiv:2609.03941v1 Announce Type: cross Abstract: RL-based post-training for reasoning models is increasingly bottlenecked by repeated fresh rollout generation, particularly in agentic settings where

HOMURA: Taming the Sand-Glass for Time-Constrained LLM Translation via Reinforcement Learning

arXiv:2601.10187v3 Announce Type: replace-cross Abstract: Large Language Models (LLMs) have achieved remarkable strides in multilingual translation but are hindered by a systemic cross-lingual verbosi

Imagination Helps Visual Reasoning, But Not Yet in Latent Space

arXiv:2602.22766v3 Announce Type: replace Abstract: Latent visual reasoning aims to mimic human's imagination process by meditating through hidden states of Multimodal Large Language Models. While rec

researcharxiv-cs-cl

Imagine-then-Plan: Agent Learning from Adaptive Lookahead with World Models

arXiv:2601.08955v3 Announce Type: replace-cross Abstract: Recent advances in world models have shown promise for modeling future dynamics of environmental states, enabling agents to reason and act wit

Introducing SINFONIA: Symplectic, slimplectic and Magnusian (Neural) Flows for Orbital Numerical Integration and Acceleration

arXiv:2609.03329v1 Announce Type: cross Abstract: Long-duration gravitational-wave modelling must resolve fast orbital motion together with slow dissipative evolution while preventing small numerical

Landmark-Based Discrimination of Injury-Associated Athlete-Sessions from Minute-Resolution Multimodal Football Monitoring Data

arXiv:2609.03790v1 Announce Type: new Abstract: Athlete monitoring data may be recorded minute by minute throughout a match or training session, while injury information may only indicate whether the

researcharxiv-cs-lg

Learning Constraints-Based Adaptive Hypergraph Neural Networks for Solving Vehicle Routing Problems

arXiv:2503.10421v2 Announce Type: replace Abstract: The application of learning based methods to vehicle routing problems has emerged as a pivotal area of research in combinatorial optimization. These

LevelSyn: Physical-Aware Logic Synthesis via Level-Asynchronous Graph Neural Networks

arXiv:2609.03594v1 Announce Type: cross Abstract: As integrated circuit technology scales into the nanometer regime, the traditional disconnect between logic synthesis and physical design has led to s

Local Ai

Local Updates, Global Learning (LUGL): Playing Games with non-incremental Learners

arXiv:2609.03660v1 Announce Type: cross Abstract: The dominance of Neural Networks (NNs) in RL is partially due to their incremental learning capability, which naturally suits the online, non-stationa

local-aiarxiv-cs-ai

Long-Horizon Consistent and Interaction-Aware World Models for Multi-Style End-to-End Driving

model-releasesarxiv-cs-ro

arXiv:2609.03225v1 Announce Type: new Abstract: End-to-end autonomous driving has increasingly adopted world model-based reinforcement learning frameworks to improve learning efficiency through extit{

Lose the Order, Keep the Hierarchy: Deordering HTN Plans

arXiv:2609.03912v1 Announce Type: new Abstract: Hierarchical Task Network (HTN) planning is a powerful planning formalism based on task decomposition. Although most of the literature studied plan gene

researcharxiv-cs-ai

Lost in Reordering: Structural Sensitivity of Multilingual LLMs under Semantics-Preserving Perturbations

model-releasesarxiv-cs-cl

arXiv:2609.03511v1 Announce Type: new Abstract: Large Language Models (LLMs) demonstrate strong multilingual reasoning performance, yet their robustness to semantics-preserving structural variation re

Agents

Medical Reasoning in the Era of LLMs: A Systematic Review of Enhancement Techniques and Applications

arXiv:2508.00669v2 Announce Type: replace-cross Abstract: The proliferation of Large Language Models (LLMs) in medicine has enabled impressive capabilities, yet a critical gap remains in their ability

agentsarxiv-cs-ai

Hardware

Mesh-Native Physics-Informed Graph Surrogates for TCAD-in-the-Loop Design Space Exploration

arXiv:2609.02988v1 Announce Type: new Abstract: High-fidelity TCAD simulation of drift-diffusion transport remains the workhorse of emerging FinFET device design, but it is computationally expensive,

hardwarearxiv-cs-lg

Mixed Data Clustering Survey and Challenges

arXiv:2512.03070v2 Announce Type: replace-cross Abstract: The advent of the big data paradigm has transformed how industries manage and analyze information, ushering in an era of unprecedented data vo

researcharxiv-cs-ai

Multi-step Proximal Policy Improvement in Offline Reinforcement Learning

arXiv:2609.03842v1 Announce Type: new Abstract: Offline reinforcement learning (RL) must reconcile two competing requirements: policy updates should stay near dataset-supported actions to keep value e

safetyarxiv-cs-lg

NeoRed: A Knowledge-Logic-Alignment Multimodal Large Language Model for Neonatal Respiratory Disease Diagnosis

arXiv:2609.03527v1 Announce Type: new Abstract: Neonatal respiratory diseases are a major cause of neonatal morbidity and mortality, posing substantial challenges in clinical practice. Despite recent

Agents

No-Regret Bayesian Optimization with Finite-Library Input-Warped Kernels

arXiv:2609.02993v1 Announce Type: new Abstract: Gaussian-process Bayesian optimization (GP-BO) excels at black-box optimization of costly functions, e.g., hyperparameter optimization (HPO) and multi-a

agentsarxiv-cs-lg

Not All Preferences Deserve Gradients: Understanding Gradient Utility in Offline Reasoning Alignment

arXiv:2602.01207v2 Announce Type: replace Abstract: Offline preference optimization aligns reasoning models from fixed chosen--rejected pairs, yet standard methods apply gradient updates from every pa

Occupancy-based Quantile Risk Control

arXiv:2609.03104v1 Announce Type: cross Abstract: Conformal risk control is an emerging framework for the safe deployment of machine learning models with finite-sample guarantees. To accommodate a bro

OctWorld: Long-Range World-Consistent Video Generation with Octree-Based 3D Mapping

arXiv:2609.03919v1 Announce Type: new Abstract: We present OctWorld, a video diffusion framework with persistent 3D memory for generating explorable, world-consistent, and high-fidelity visual scenes.

researcharxiv-cs-cv

Tutorials

P-CORE: Self-Supervised Surface Consistency for Point-Based Neural Editing

arXiv:2609.03349v1 Announce Type: new Abstract: Advances in neural rendering have enabled high-fidelity multi-view reconstruction of 3D scenes. However, free-form non-rigid shape editing remains a sig

tutorialsarxiv-cs-cv

PaperScout: An Autonomous Agent for Academic Paper Search with Process-Aware Sequence-Level Policy Optimization

arXiv:2601.10029v3 Announce Type: replace Abstract: Academic paper search is a fundamental task in scientific research, yet most existing approaches organize retrieval around predefined workflows or s

PeroMAS: A Multi-agent System of Perovskite Material Discovery

arXiv:2602.13312v2 Announce Type: replace-cross Abstract: As a pioneer of the third-generation photovoltaic revolution, Perovskite Solar Cells (PSCs) are renowned for their superior optoelectronic per

Principia: Relational Physics Tests for Video Models

model-releasesarxiv-cs-cv

arXiv:2609.04200v1 Announce Type: new Abstract: Evaluating physical reasoning in video models is difficult because absolute motion measurements depend on frame rate, object scale, and camera calibrati

Privacy Leakage in Federated Learning: Gradient-Based Client Identity Inference and Defenses for Inertial Sensing in Vehicular Edge Networks

arXiv:2609.02971v1 Announce Type: cross Abstract: As vehicular networks move toward 5G/6G edge intelligence, federated learning (FL) is widely promoted as a privacy-preserving way for vehicles and inf

Privacy-Preserving Heterogeneous Multi-LLM Federated Inference for Cognitive Diagnosis

arXiv:2609.02947v1 Announce Type: cross Abstract: Significant challenges remain in AI-driven educational systems in balancing privacy preservation with accurate cognitive diagnosis. To overcome this,

Local Ai

Privacy-Preserving Topology-Guided Safety for LLM-Based Multi-Agent Systems via Federated Graph Learning

arXiv:2609.02967v1 Announce Type: cross Abstract: Topology-guided safeguards for LLM-based multi-agent systems (MAS) train a GNN over the inter-agent communication graph to localize risky agents and i

local-aiarxiv-cs-ai

Quantum Implicit Neural Representations for Novel View Synthesis

arXiv:2601.05250v2 Announce Type: replace Abstract: Quantum implicit neural representations have recently emerged as compact function approximators for continuous visual signals. In parallel, Neural R

safetyarxiv-cs-cv

R^{2}Adapter: A Routing and Rewriting Adapter for Efficient Hybrid RAG

arXiv:2609.02894v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) has become a prevailing paradigm for enhancing Large Language Models (LLMs) with non-parametric knowledge. Vanilla

researcharxiv-cs-cl

Local Ai

RATL: Learning from Retrieved Residuals for Robust Multivariate Time-Series Forecasting

arXiv:2609.03937v1 Announce Type: cross Abstract: Retrieval-augmented generation (RAG) complements parametric models with retrieved external evidence. The same idea is attractive for continuous-output

local-aiarxiv-cs-ai

Applications

RECAST: Expanding the Boundaries of LLMs' Complex Instruction Following with Multi-Constraint Data

arXiv:2505.19030v5 Announce Type: replace Abstract: Large language models (LLMs) are increasingly expected to tackle complex tasks, driven by their expanding applications and users' growing proficienc

applicationsarxiv-cs-ai

Reflect-SQL: A Self-Reflection Based Framework for Text-to-SQL

arXiv:2609.02944v1 Announce Type: cross Abstract: Democratizing data access through natural language is a crucial goal for modern enterprises, but the practical adoption of Text-to-SQL is critically h

Reliable Selection of Heterogeneous Treatment Effect Estimators

arXiv:2511.18464v2 Announce Type: replace-cross Abstract: We study the problem of selecting the best heterogeneous treatment effect (HTE) estimator from a collection of candidates in settings where th

researcharxiv-cs-lg

Remember and Reweight: Enhancing Multi-Agent Debate with Experience Memory and Confidence Estimation

arXiv:2609.03619v1 Announce Type: cross Abstract: Multi-agent debate (MAD) improves the reasoning capabilities of large language models by having multiple agents iteratively refine their responses thr

Revisiting Topological Graphs for Macro Action based Closed-loop Reinforcement Learning of Vision Language Navigation in Continuous Environment

arXiv:2609.03906v1 Announce Type: new Abstract: Vision-Language Navigation in Continuous Environments (VLN-CE) requires an agent to follow natural language instructions through unseen environments. Ex

safetyarxiv-cs-ro

RoboTok: An Internet-Scale Data Engine for Human Demonstration Retrieval and Dexterous Manipulation Learning

arXiv:2609.03199v1 Announce Type: new Abstract: Robot learning increasingly depends on broad and diverse demonstrations, yet collecting robot data remains expensive and poorly suited to covering the l

safetyarxiv-cs-cv

Robust PAC Learning of Concurrent Stochastic Games

arXiv:2609.04189v1 Announce Type: new Abstract: We introduce the first Probably Approximately Correct (PAC) learning framework for general-sum concurrent stochastic games (CSGs) with transition uncert

Tutorials

RuleMem: Active Rule Memory for Long-Term Conversational Agents

arXiv:2609.03915v1 Announce Type: new Abstract: Question answering agents in long-term conversations must reason over massive, temporally dispersed dialogue histories. However, existing memory mechani

tutorialsarxiv-cs-cl

SafeRI: Recognition and Intervention for Token-Level Safety Intervention in Large Vision Language Models

arXiv:2609.03544v1 Announce Type: new Abstract: Existing safety alignment methods for vision-language models usually modify the model behavior globally: once the safety parameters are trained or loade

safetyarxiv-cs-cv

Scaling Laws, Tabular Data and Actuarial Ratemaking Models

arXiv:2609.03106v1 Announce Type: new Abstract: Scaling laws in modern deep learning describe how held-out loss improves as model capacity, training data, and compute increase, often following power-l

Sequential Beats Joint: On the Interplay between On-Policy Distillation and RLVR

arXiv:2609.04108v1 Announce Type: cross Abstract: Reinforcement learning with verifiable rewards (RLVR) and on-policy distillation (OPD) have emerged as two dominant methods for post-training reasonin

SGD-KV: Summarization Guided KV Cache Compression

arXiv:2609.03235v1 Announce Type: new Abstract: Large language models (LLMs) face severe memory bottlenecks in long-context inference due to the linearly growing size of key-value (KV) caches. Existin

researcharxiv-cs-cl