Search: “evaluation”

Large Language Model Assisted Transportation Planning through a Differentiable User Equilibrium Layer

arXiv:2610.16140v1 Announce Type: new Abstract: Transportation planning has traditionally required substantial expertise in network modeling, traffic assignment, and optimization. As a result, strateg

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LATCH: LLM-Assisted Timing Closure Harness for Post-Route FPGA Optimisation

DGX agent

arXiv:2610.16625v1 Announce Type: new Abstract: Post-route FPGA timing closure remains expert-dependent and computationally expensive. We present LATCH (LLM-Assisted Timing Closure Harness), a two-lay

agentsarxiv-cs-ai

15 Oct 2026

Learnable Hodge-Laplacian Driven Mixture of Experts for Steady-PDE Surrogates on Coarse Unstructured Meshes

arXiv:2610.20585v1 Announce Type: cross Abstract: Current approaches for steady partial differential equations surrogate models on unstructured meshes apply a single mixing mechanism to the whole solu

Learning by Examples: Power Grid Steady State Analysis with a Tabular Foundation Model

arXiv:2610.20462v1 Announce Type: new Abstract: Foundation models have shown strong generalization across scientific domains, but their use in power systems remains largely task-specific. We investiga

Tutorials

Learning Keypoint Constraints from Visual Demonstrations for Safe Motion Planning

arXiv:2610.19295v1 Announce Type: new Abstract: We present Keypoint Constraint Learning (KCL), a framework for learning task-relevant motion constraints from visual demonstrations and for planning saf

tutorialsarxiv-cs-ro

Learning Proposition-Level Links from Sentence-Level Supervision for Neuro-Symbolic NLI

arXiv:2610.15158v2 Announce Type: replace Abstract: We study neuro-symbolic natural language inference (NLI) with independently translated propositional representations of the premise and hypothesis.

Learning Visual Speech Representations via Cross-Modal Distillation and Joint Face-Lip Modeling

arXiv:2610.19559v1 Announce Type: new Abstract: Lipreading remains challenging due to the inherent ambiguity of visual speech cues and their sensitivity to head pose and video resolution. In this work

Lifted State Policy Optimization: Internalizing Self-Correction through Transition Geometry

arXiv:2610.20350v1 Announce Type: cross Abstract: Preference optimization ranks final answers and trajectory RL maximizes aggregate returns, yet neither credits the local change that turns a flawed re

Likelihood Is Not Authorship: Can We Reliably Measure Human Contribution in AI-Assisted Writing?

arXiv:2610.19767v1 Announce Type: new Abstract: AI-text detection generally asks whether a machine wrote a text. As AI becomes an increasingly integral and accepted part of writing, the more relevant

Linearly Convergent Algorithms for Nonsmooth Problems with Unknown Smooth Regions

model-releasesarxiv-cs-lg

arXiv:2507.19465v2 Announce Type: replace-cross Abstract: We develop efficient algorithms for optimizing piecewise smooth (PWS) functions when their smooth regions are unknown to the algorithm. For co

Lingdan-V2: Large language models for clinically grounded reasoning in traditional Chinese medicine

model-releasesarxiv-cs-ai

arXiv:2610.14705v1 Announce Type: cross Abstract: Large language models have advanced medical reasoning, but clinically grounded reasoning in traditional Chinese medicine (TCM) remains challenging bec

Logit Leakage through Floating-Point Bias Addition

model-releasesarxiv-cs-ai

arXiv:2610.16790v1 Announce Type: cross Abstract: Language model APIs can expose token-specific biases while withholding logits and token probabilities. Existing bias-based extraction recovers relativ

Long-Horizon RL Needs Muon

arXiv:2610.20256v1 Announce Type: new Abstract: Long-horizon agents must coordinate reasoning, tool use, and environment feedback over extended interactions. Learning from sparse outcome rewards requi

Lotus: Learning to Understand Time-series by Learning to Forecast

arXiv:2610.18877v1 Announce Type: cross Abstract: Time-series language models typically align numerical signals with language using labels, captions, or question-answer pairs. Although such supervisio

LYNX: Analytical Program Synthesis via Grounding and Closed-Loop Refinement

arXiv:2610.14777v1 Announce Type: new Abstract: LLM-powered data analytics aims to translate natural language instructions into executable analytical programs over underlying data. However, existing a

MADDIE: Multi-Agent Drug Discovery Engine

arXiv:2610.16975v1 Announce Type: new Abstract: Drug discovery remains a resource-intensive and time-consuming process, involving billions of dollars and a decade of development to advance a drug to m

Making Language the Low-Rate Code of Vision: Successive Refinement from Words to Pixels

arXiv:2610.16552v1 Announce Type: new Abstract: An ordered visual code lets a short prefix stand in for an image, and the training loss decides what that prefix contains. Under pixel reconstruction th

MCAIR: Monitoring and Correcting Agent Unfaithfulness via Internal Representations

arXiv:2610.19679v1 Announce Type: cross Abstract: Large Language Model (LLM)-based agents have demonstrated remarkable capabilities in completing complex tasks through multi-step reasoning and tool in

agentsarxiv-cs-lg

Measuring the Inference Energy Efficiency of Open-Weight LLMs across Benchmarks, Reasoning Modes, and Hardware

model-releasesarxiv-cs-ai

arXiv:2610.14389v1 Announce Type: new Abstract: Benchmark scores tell us what an LLM can do, but not how much energy is required to deliver that capability. We directly measure this trade-off for 86 o

MemDuet: Learning Dual-Process Memory for Long-Context Reasoning

arXiv:2610.19928v1 Announce Type: new Abstract: Reasoning over infinitely long documents is becoming a reality with recurrent memory agents. However, increasing context length exacerbates the trade-of

MemeTrace: A Multimodal LLM-Based Agent for Safety-Aware Meme Provenance Analysis

arXiv:2610.19267v1 Announce Type: cross Abstract: Online memes are often carriers of unsafe content such as disinformation and propaganda. Their rapid evolution in response to news events and strong d

MIPS: Mitigating Mode Collapse in Reinforcement Learning for Large Outcome Spaces

arXiv:2610.19457v1 Announce Type: new Abstract: Expected-reward maximization in reinforcement learning concentrates probability mass on a few outcomes, even in tasks that require many distinct, high-q

MIRAGE: Metric Inference and Reliability-Aware Gaussian Estimation from Feed-Forward Vision

arXiv:2610.12568v2 Announce Type: replace Abstract: Feed-forward 3D priors enable high-quality reconstruction from image streams but often lack reliable metric scale and suffer from long-term trajecto

Mitigating Cross-Modal Hallucinations by Correcting Modality Misrouting in Omnimodal LLMs

arXiv:2610.18141v1 Announce Type: new Abstract: Omnimodal large language models (OLLMs) are susceptible to cross-modal hallucinations under audio-visual interference. We find that, for a substantial f

Mixed Poisson diffusion models and application to posterior sampling

arXiv:2610.20218v1 Announce Type: cross Abstract: Diffusion models are a powerful framework for learning complex probability distributions. While widely used diffusion models for continuous data rely

MixLID: Token-Level Language Identification in Mixed-Language Text

arXiv:2610.16601v1 Announce Type: cross Abstract: Processing multilingual text requires both identifying a broad range of languages and distinguishing the language of each token in inputs containing m

Tutorials

MMKG-R1: Constructing Multimodal Knowledge Graphs via Reinforcement Learning

arXiv:2610.19341v1 Announce Type: new Abstract: Multimodal knowledge graphs (MMKGs) organize information across different modalities to support multimodal Graph Retrieval-Augmented Generation (RAG), w

tutorialsarxiv-cs-cv

Model What Matters: Decision-Guided Selective World Modeling for Language Agents

arXiv:2610.19642v1 Announce Type: cross Abstract: Reinforcement learning provides a direct mechanism for optimizing task objectives in large language model-driven agents, but task rewards are typicall

MolLean: A Process-Verifiable Language for Chemical Reasoning

arXiv:2610.20459v1 Announce Type: new Abstract: Chemical chain-of-thought can contain hallucinated structural and property claims. We thereby introduce MolLean, a process-verifiable language that grou

agentsarxiv-cs-cl

MoMaTune: Model, Match, Then Tune Language Models for Numerical Records

arXiv:2610.15235v1 Announce Type: new Abstract: Despite remarkable progress in language understanding and generation, decoder language models continue to exhibit striking failures on numerical data. N

Moral Combat: Exploiting Moral Foundations Theory to Jailbreak LLMs

arXiv:2610.19587v1 Announce Type: new Abstract: Social psychology has long described how people can be persuaded to interpret a harmful act as moral. Recent research suggests that Large Language Model

More Than Seeing: Vision as Scalable Anchors in Native Multimodal Pre-Training

arXiv:2610.19443v1 Announce Type: new Abstract: Native multimodal pre-training trains a single model from scratch on text and multimodal data, enabling it to understand both language and visual inputs

MorphAct: Robot Policies Morphing with the Worlds They Act In

model-releasesarxiv-cs-ro

arXiv:2610.20019v1 Announce Type: new Abstract: Progress toward general intelligence in the physical world requires scaling robot learning across diverse environments and interactions. However, existi

Local Ai

MUCO: A Mani-Unit-Structured Manipulation Framework for Compositional Long-Horizon Robot Tasks

arXiv:2610.19913v1 Announce Type: new Abstract: Learning and executing long-horizon robot manipulation as complete task trajectories raises data-collection costs, lim?its capability reuse, and causes

local-aiarxiv-cs-ro

NavAble: A Large-Scale Dataset and Synthetic Data Generation Pipeline for Blind Navigation

arXiv:2610.19330v1 Announce Type: new Abstract: Reliable recognition of accessibility-critical objects (e.g., audible pedestrian signals, door-activation buttons, and handrails) is essential for assis

On Global Joint Lower Bounds in Zeroth-Order Nonconvex Optimization

arXiv:2610.19652v1 Announce Type: new Abstract: Recent work has sought to transfer first-order nonconvex optimization guarantees to zeroth-order methods through gradient estimators, typically incurrin

One Task, Many Interfaces: Simple Cross-Interface Consistency Training Improves LLM Agent Robustness

arXiv:2610.20576v1 Announce Type: cross Abstract: Post-training binds the competence of an LLM agent to the interface it was trained on. Semantics-preserving perturbations of that interface, such as r

OneLA: Learning Many Worlds from Latent Actions

arXiv:2610.20160v1 Announce Type: new Abstract: Learning world models across diverse domains calls for a unified control space, yet ac- tion interfaces vary across domains and action annotations are o

safetyarxiv-cs-cv

OpenDepth: Repurposing Image Editing Priors for Robust Open-World Monocular Depth Estimation

arXiv:2610.17610v2 Announce Type: new Abstract: Recently, the integration of generative priors has revolutionized Monocular Depth Estimation (MDE), achieving state-of-the-art (SOTA) performance with r

Optimization for One, Feasibility for Most: Decoupling Optimization from Feasibility in Chance-Constrained Programs

model-releasesarxiv-cs-lg

arXiv:2610.19027v1 Announce Type: cross Abstract: Chance-constrained stochastic programs (CCSPs) require solutions that satisfy uncertain constraints with high probability. Standard approaches either

Outcome-Routed Distillation and Reinforcement Learning for Diffusion Language Models

arXiv:2610.19271v1 Announce Type: new Abstract: On-policy distillation provides dense supervision on the student's own samples, but its targets still come from the teacher. Verifier reinforcement lear

PA1-OPD: One-Step Prefix-Augmented On-Policy Distillation for Language Model Pretraining

arXiv:2610.19601v1 Announce Type: new Abstract: Knowledge distillation (KD) improves language-model pretraining by matching teacher distributions at corpus prefixes, but provides no direct supervision

PACER: Process-Aware VLA Policy Learning from Human Corrections for Robotic Disassembly

model-releasesarxiv-cs-ro

arXiv:2610.19248v1 Announce Type: new Abstract: Robotic disassembly of end-of-life (EoL) products requires robots to accommodate product variation, follow prerequisite sequences, and approach componen

PANINI-DR: Controlled Deep Research through Generative Semantic Workspaces

arXiv:2610.15208v1 Announce Type: cross Abstract: Deep research requires connecting multiple steps of search, reasoning, and computation, with intermediate findings guiding what to investigate next. A

Penumbra: Sample-Efficient Adversarial Search for Regulatory Obligations

arXiv:2610.04693v2 Announce Type: replace Abstract: Agents are entering finance, healthcare and law, sectors where a violation leaves no lexical signature and carries real penalties. Whether an omissi

Physical Layer Anomaly Detection via Adaptive Gaussian Mixture Model

model-releasesarxiv-cs-lg

arXiv:2610.18946v1 Announce Type: cross Abstract: Physical-layer spoofing attacks pose a critical threat to wireless localization systems by manipulating channel state information (CSI). Detecting suc

Physics-Guided Multi-Fidelity Surrogate Modeling for Natural Supercavity Geometry of an Axisymmetric Conical Cavitator

arXiv:2610.18886v1 Announce Type: cross Abstract: Natural supercavitation behind conical cavitators generates a vapor-filled envelope that, when sustained over the full body of a high-speed underwater

Physics-Shaped, Not Physical: Auditing Physics-Guided Underwater Image Restoration

arXiv:2610.19763v1 Announce Type: new Abstract: Physics-guided networks for underwater image restoration predict transmission and backscatter and invert the image-formation model, yet rarely test whet

safetyarxiv-cs-cv