Search: “evaluation”

SuPER-Mamba: Surprisal Prioritization for Extended-Context Routing in Mamba

arXiv:2610.16636v1 Announce Type: cross Abstract: State space models provide efficient linear-complexity processing for long sequences, but their performance frequently degrades as context length grow

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Agents

SwarmRSI: Recursive Self-Improvement through Evolving Scientific Agent Swarm

DGX agent

arXiv:2610.20431v1 Announce Type: cross Abstract: Recursive self-improvement (RSI) in scientific research aims to improve agents' research capabilities through their own experimental experience. Scien

agentsarxiv-cs-cl

15 Oct 2026

TEX-MEX: Similarity-Guided Temporal Contrastive Learning for Time Series

model-releasesarxiv-cs-lg

arXiv:2610.19557v1 Announce Type: new Abstract: Contrastive learning for time series depends on deciding which pairs of inputs should be treated as similar and dissimilar. Because few augmentations re

Text-Informed Training Data Filtering for Enhanced Virtual Flow Meter Performance

arXiv:2610.19860v1 Announce Type: cross Abstract: In sectors such as energy, aquaculture and chemical processing, the effectiveness of both mechanistic and data-driven models is frequently limited by

researcharxiv-cs-lg

TextualRL: Textual Reinforcement Learning for Context Management

arXiv:2610.18216v1 Announce Type: cross Abstract: LLM agents can adapt to task feedback by revising the textual context that guides their behavior, without changing their model parameters. However, tu

TextVerifier: Seeing Beyond Recognition to Verify Chinese Text Rendering

model-releasesarxiv-cs-cv

arXiv:2610.19551v1 Announce Type: new Abstract: Text-to-image models increasingly generate readable Chinese text that still contains local rendering defects, such as a character with an extra or missi

The Agentic Scientist: Orchestrating Coding Agents for Automated Scientific (Co-)Discovery

arXiv:2610.18933v1 Announce Type: cross Abstract: Modern coding agents are fundamentally reshaping the role of human input for computational research: they write code, launch in silico experiments, an

agentsarxiv-cs-cl

The Imperishable Record, Forgiveness, and the Future of Criminal Justice

arXiv:2610.15499v1 Announce Type: cross Abstract: Digital technologies can preserve records of wrongdoing indefinitely, and AI can give those records continuing influence over a person's future. We de

researcharxiv-cs-ai

The Invisible Leash: Why RLVR May or May Not Escape Its Origin

arXiv:2507.14843v5 Announce Type: replace-cross Abstract: Recent advances highlight Reinforcement Learning with Verifiable Rewards (RLVR) as a promising approach to enhancing LLM capabilities. However

The Sharp Directions Are Against You: Curvature Analysis of Activation Steering

arXiv:2610.16084v1 Announce Type: new Abstract: Activation steering adds a vector to a language model's internal representations at inference time. It is a lightweight alternative to fine-tuning for b

The Smart Buildings Challenge: Learning Foundation Models for Real-World Optimization at Scale

arXiv:2610.18511v1 Announce Type: new Abstract: Buildings cause nearly 40% of carbon emissions in the US. Of total building emissions, HVAC systems are responsible for approximately 40-60% and account

Titan-Llama: Retrofitting Pre-trained LLMs with External Neural Memory Modules

arXiv:2610.19210v1 Announce Type: new Abstract: Transformers are efficient to pre-train at scale because attention permits parallel computation across sequence positions, but long-context inference re

Toward a Universal Characterization of Sudoku Puzzle Difficulty

arXiv:2507.21137v2 Announce Type: replace Abstract: In this paper we try to answer the question 'What constitutes Sudoku difficulty rating across different Sudoku websites?' Using two distinct methods

researcharxiv-cs-ai

Local Ai

Toward Fine-Grained Forgetting:Attribute Unlearning for Multimodal Large Language Models

arXiv:2608.01008v2 Announce Type: replace Abstract: Multimodal large language models (MLLMs) can memorize and disclose sensitive information, motivating machine unlearning to remove designated knowled

local-aiarxiv-cs-ai

Toward System One Clinical Intelligence: Parameter-Efficient Fine-Tuning and Counterfactual Explainability of Decision Foundation Models

arXiv:2610.15029v1 Announce Type: cross Abstract: Automated disease classification from patient-reported symptoms requires balancing the speed of lightweight discriminative models against the contextu

Towards Agentic Robots: Model, Data, Environment, and Harness

arXiv:2610.20442v1 Announce Type: new Abstract: Foundation models are driving a paradigm shift in robotic intelligence, moving beyond low-level action prediction to goal-directed orchestration of data

agentsarxiv-cs-ro

Trace-to-Architecture: Capability Bottleneck Diagnosis for Harness Revision

arXiv:2610.16725v1 Announce Type: new Abstract: Improving an LLM agent requires knowing what to change when it fails. Similar failures can require different fixes, and resolving one problem can expose

agentsarxiv-cs-ai

TRACER: Trace-Regularized Training Against Indirect Prompt Injection

arXiv:2610.19133v1 Announce Type: new Abstract: Indirect prompt injection uses untrusted retrieved content, tool outputs, or agent messages to override an LLM's intended behavior. We show that defense

agentsarxiv-cs-lg

Tracing Morphology, Semantics, and Divergence in Language Acquisition

arXiv:2610.19041v1 Announce Type: cross Abstract: Understanding the dynamics of language acquisition in Large Language Models (LLMs) is crucial for uncovering how statistical representations evolve in

researcharxiv-cs-cl

Transparent Information Flow Modeling for Role-Aware AI Act Assessment

arXiv:2610.16916v1 Announce Type: new Abstract: The European Union's Artificial Intelligence Act introduces a structured framework for governing high-risk AI systems, emphasizing transparency, risk ma

Tread: A Visuo-Inertial Framework for Terrain and Locomotion Context-Aware Gait-Phase and Speed Estimation in Wearable Robotics

arXiv:2610.19067v1 Announce Type: new Abstract: A wearable assistive robot must continuously estimate terrain, locomotion mode, gait phase, and walking speed. These quantities are commonly addressed b

researcharxiv-cs-ro

Local Ai

TreeSpark: Learning to Draft the Trees You Verify for Speculative Decoding

arXiv:2610.20175v1 Announce Type: new Abstract: Parallel drafters such as DFlash and DSpark reduce proposal latency, but early mismatches limit how much of each block can be accepted. Retaining altern

local-aiarxiv-cs-cl

Typed Decision Models on Tabular Data

arXiv:2610.19536v1 Announce Type: new Abstract: Typed decision models are language models that answer a question with a fixed set of possible answers by returning a probability for each answer instead

researcharxiv-cs-cl

VC-OPD: Visual Counterfactual On-Policy Distillation for Grounded Vision-Language Reasoning

arXiv:2610.14939v1 Announce Type: new Abstract: GRPO-style reinforcement learning has advanced vision-language reasoning, but its sequence-level rewards provide limited credit assignment for individua

Verification as an Architectural Layer for LLM Agents: A V-Model Design, and a Pilot Study of Its Deterministic Core

arXiv:2609.31937v2 Announce Type: replace-cross Abstract: Large language model (LLM) agents built on the ReAct pattern concentrate four responsibilities in one model: selecting a strategy, choosing ea

Verifier-Grounded Agentic RL for Provably Correct Code

arXiv:2610.19298v1 Announce Type: new Abstract: Reinforcement learning for code usually rewards passing tests, which a model can do while remaining wrong on the inputs the tests do not cover. A progra

safetyarxiv-cs-lg

Video Depth Anything: Consistent Depth Estimation for Super-Long Videos

arXiv:2501.12375v4 Announce Type: replace Abstract: Depth Anything has achieved remarkable success in monocular depth estimation with strong generalization ability. However, it suffers from temporal i

researcharxiv-cs-cv

VIGOR-MPC: Vision-Guided Objective Regulation MPC

arXiv:2610.20333v1 Announce Type: new Abstract: Controlling an agent in an environment solely perceived through onboard vision is challenging: perception yields noisy, variable-length, and partially o

agentsarxiv-cs-ro

Virtual-Alloy Physics-Aware Semantic System for extrapolative prediction of perovskite solar cells

model-releasesarxiv-cs-lg

arXiv:2610.18949v1 Announce Type: cross Abstract: Existing machine-learning models for perovskite solar cells struggle to predict devices made from new materials. Most treat device layers as arbitrary

Virtual Head Attention

arXiv:2610.17959v1 Announce Type: cross Abstract: The design of attention mechanisms in long-context large language models faces an ``impossible triangle'' among KV cache size, training and prefill FL

VisibilitySplat: Ray-Traced Occlusion for Relighting with 3D Gaussian Splatting

arXiv:2610.19847v1 Announce Type: new Abstract: We address inverse rendering with 3D Gaussian Splatting (3DGS) by introducing explicit visibility modeling for relighting as well as material and light

researcharxiv-cs-cv

Visible but Not Avoided: State-Dependent Re-Proposal of Rejected Candidates in Catalog-Based LLM Optimization Loops

arXiv:2610.15738v1 Announce Type: new Abstract: LLM optimization loops often show the proposer the candidates it has already tried and rejected, but leave it to the proposer to avoid them. We ask whet

agentsarxiv-cs-ai

WeatherBridge: Forecast-Aware Multi-Source Input Adaptation for Pretrained Weather Forecasting Models

arXiv:2610.14863v1 Announce Type: new Abstract: Data-driven weather forecasting models are commonly trained on ERA5, yet operational deployment must use timely initial states from physics-based numeri

WeGR: Unified Generative Retrieval for Industrial Search Systems in WeChat

arXiv:2610.16979v1 Announce Type: cross Abstract: Generative retrieval (GR) offers a promising paradigm for industrial search by unifying candidate generation within an autoregressive framework. Howev

Weighted Ensemble Sampling for Rare-Event Estimation in Language Models

arXiv:2610.19202v1 Announce Type: new Abstract: Rare but severe failures of large language models can become practically significant at deployment scale. Estimating their probabilities with direct Mon

safetyarxiv-cs-cl

What Makes a Social Agent's Interactions Effective? Learning from Verifiable Outcomes in Paired Worlds

arXiv:2610.20195v1 Announce Type: new Abstract: Effective social interaction requires more than fluent responses: agents must reach plans that fit the participants' needs and circumstances. Existing e

What Matters for World Modeling in Vision-Language-Action Models?

arXiv:2610.19825v1 Announce Type: cross Abstract: Integrating world models into Vision-Language-Action models (VLAs) has emerged as a promising direction, enabling policies to anticipate future dynami

safetyarxiv-cs-cv

What the Model Cannot See: Covert and Provable Text Invisibility in LLMs

arXiv:2610.15883v1 Announce Type: cross Abstract: Text wrapped in a trigger can be made behaviorally invisible to a language model: omitted from summaries and quotations, ignored in question answering

When Agents Talk, Secrets Travel: Topology-Driven Leakage and Recipient-Conditioned Sanitization in Multi-Agent LLM Systems

arXiv:2610.16039v1 Announce Type: cross Abstract: Multi-agent LLM systems (MALS) introduce a privacy-leakage problem that conventional sensitivity-based defenses miss, since information disclosed to o

agentsarxiv-cs-ai

When Does Momentum Help in Reinforcement Learning with Verifiable Rewards?

arXiv:2610.20413v1 Announce Type: new Abstract: Momentum is a classical tool for accelerating convex optimization and a standard component of modern large language model training. Yet recent empirical

safetyarxiv-cs-lg

When Does Task-Aware Imputation Matter? An Analysis of Robustness Under Train-Test Mismatch

arXiv:2610.20342v1 Announce Type: new Abstract: Missing data is a pervasive challenge in machine learning, often degrading predictive performance and complicating model deployment. Most existing appro

researcharxiv-cs-lg

When Occupation-derived Skills Don't Help: On the Limits of Skill-Augmented Career Path Prediction

arXiv:2610.20186v1 Announce Type: new Abstract: Skills are widely assumed to play a central role in career transitions, motivating their use in career path prediction (CPP) systems. In this work, we c

Where Do LLM Ensemble Gains Come From? Decomposing Candidate Value, Diversity, and Aggregation

arXiv:2610.18786v1 Announce Type: cross Abstract: LLM ensemble gains are often measured against a single baseline, but the value attributed to additional candidates can change with the comparison used

researcharxiv-cs-ai

Where to Start, How to Move: Analyzing Curricula under GRPO for Long-Horizon LLM Agents

arXiv:2610.19349v1 Announce Type: cross Abstract: Group Relative Policy Optimization (GRPO) provides no reward-relative learning signal when all rollouts receive identical rewards. In long-horizon tas

safetyarxiv-cs-cl

Which Metadata Matters for LLM Tool Selection in MCP? Evidence from Controlled Factor-Level Interventions

arXiv:2610.14334v1 Announce Type: new Abstract: In Model Context Protocol (MCP) systems, LLMs select tools from metadata rather than from their implementations. Names and descriptions summarize what a

Local Ai

Why Agentic Workflows Fail: A Taxonomy Derived from Literature and Empirical Data

arXiv:2610.17418v1 Announce Type: cross Abstract: Agentic workflows combine large language models with planning, memory, tools, execution environments, and iterative feedback. Their failures are diffi

local-aiarxiv-cs-ai

Tutorials

World Models Need a Physical Registry: Learning Internal Predictive States for Physically Plausible World Models

arXiv:2610.16365v1 Announce Type: new Abstract: Video world models must generate physically plausible futures, not just realistic frames. Existing approaches typically use semantic, physical, or predi

tutorialsarxiv-cs-ai

Applications

1Step-WAM: Your World Action Model but Faster using 1-Step Action Generation