Search: “framework”

arXiv:2610.17689v1 Announce Type: new Abstract: Serverless inference is emerging as an efficient deployment model for Large Language Models (LLMs) due to its ability to elastically scale resources, im

hardwarearxiv-cs-ai

Local Ai

STP-GUI: Spatially-Aware Token Pruning for Efficient Web-GUI Agents

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DGX agent

arXiv:2610.20390v1 Announce Type: new Abstract: With the rapid development of vision-language models (VLMs), Web-GUI agents have achieved promising performance in interacting with real-world interface

local-aiarxiv-cs-cv

15 Oct 2026

Strategy Executability in Mathematical Reasoning: Leveraging Human-Model Differences for Effective Guidance

arXiv:2602.22583v2 Announce Type: replace Abstract: Example-based guidance is widely used to improve mathematical reasoning at inference time, yet its effectiveness is highly unstable across problems

Structural Chain-of-Thought: Reasoning with Executable Computational Graphs

arXiv:2610.15107v1 Announce Type: new Abstract: Chain-of-thought prompting enables reasoning in large language models but produces explanations that are difficult to verify, expensive to generate, and

researcharxiv-cs-ai

Structure-Preserving Document-Level Data Augmentation via Discourse Parsing

arXiv:2610.19497v1 Announce Type: new Abstract: Data augmentation (DA) plays a vital role in improving model performance in low-resource or limited-supervision scenarios within Natural Language Proces

researcharxiv-cs-cl

Subgraph-Aware Training of Language Models for Knowledge Graph Completion Using Structure-Aware Contrastive Learning

arXiv:2407.12703v5 Announce Type: cross Abstract: Fine-tuning pre-trained language models (PLMs) has recently shown a potential to improve knowledge graph completion (KGC). However, most PLM-based met

safetyarxiv-cs-ai

SwarmRSI: Recursive Self-Improvement through Evolving Scientific Agent Swarm

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

TANGO: RNA Topology and Geometry Co-Design

arXiv:2610.20277v1 Announce Type: new Abstract: Designing RNA sequences that satisfy target tertiary-structure objectives is an important problem in RNA engineering, with broad applications in synthet

safetyarxiv-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

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

model-releasesarxiv-cs-cl

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 Reasoning Trap -- Logical Reasoning as a Mechanistic Pathway to Situational Awareness

model-releasesarxiv-cs-cl

arXiv:2603.09200v2 Announce Type: replace-cross Abstract: Situational awareness, the capacity of an AI system to recognize its own nature, understand its training and deployment context, and reason st

The Silent Failures in Agentic Data Science

arXiv:2610.14115v1 Announce Type: new Abstract: Large language models have significantly lowered the barrier to writing code. Naturally, this has also led to the development of data science agents tha

Think in Strategies, Act with Tools: Traceable Agentic Optimization for Combinatorial Problems

arXiv:2610.14736v1 Announce Type: new Abstract: Optimization by PROmpting (OPRO) directly leverages Large Language Models (LLMs) to generate candidate solutions through natural-language prompting. How

ThreadBench: Benchmarking Realism in Agentic Simulation of Real-world Discussions

arXiv:2606.14715v2 Announce Type: replace-cross Abstract: LLM agents are increasingly used to simulate real-world interactions, but it remains unclear whether simulated behaviors preserve the content

TorchSpin: Differentiable Electron Paramagnetic Resonance Simulation in PyTorch

model-releasesarxiv-cs-lg

arXiv:2610.18924v1 Announce Type: cross Abstract: Interpreting electron paramagnetic resonance (EPR) spectra commonly requires repeated forward simulation and optimization of spin Hamiltonian paramete

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 Merging-conditional Backdoor Unalignment against Large Language Models

arXiv:2610.14701v1 Announce Type: cross Abstract: Model merging has become widely adopted for enhancing the task-specific performance of Large Language Models (LLMs) without additional training. While

Applications

Towards Resilience: Slice-Driven Orchestration of Mobile IoMT in 6G-Edge-Continuum

arXiv:2610.17296v1 Announce Type: new Abstract: Emerging healthcare services, such as real-time diagnostics, remote health monitoring and computer-assisted surgery, require stringent Quality of Servic

applicationsarxiv-cs-ai

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

TRAP: Tool-result Replay Attack for Probing Misbinding in LLM Agents

arXiv:2610.16333v1 Announce Type: new Abstract: As AI agents increasingly act through external tools, tool results are no longer simple outputs but execution artifacts that must remain correctly assoc

Tree-Structured Synergy of Large Language Models and Bayesian Optimization for Efficient CASH

arXiv:2601.12355v3 Announce Type: replace Abstract: To lower the expertise barrier in machine learning, the AutoML community has focused on the CASH problem, which jointly automates algorithm selectio

safetyarxiv-cs-lg

TreeFlex: Agents Navigating Their Own Search Trees

model-releasesarxiv-cs-cl

arXiv:2610.20334v1 Announce Type: cross Abstract: A ReAct-style agent accumulates observations, intermediate results, and failed attempts in a single context. As this context grows, stale and off-path

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

UDHRBench: Benchmarking Human Rights in Large Language Models

arXiv:2610.15179v1 Announce Type: cross Abstract: Large language models are increasingly deployed in contexts requiring adherence to ethical and legal norms, yet their alignment with internationally r

Upstream Influence, Downstream Re-Anchoring in LLM Agent Chains

arXiv:2610.17723v1 Announce Type: new Abstract: People act on evaluative judgments produced by LLM agents, and in multi-agent systems those judgments pass through several agents before reaching a pers

Tutorials

VascuSR: Iterative Anatomy-Aware Diffusion for CT Super-Resolution

arXiv:2610.20509v1 Announce Type: new Abstract: Generative super-resolution (SR) can recover sharp detail in computed tomography (CT) images from severely downsampled observations, but the missing hig

tutorialsarxiv-cs-cv

Applications

Vela: User Behavior as Supervision Sparks LLM Intelligence

arXiv:2610.14709v1 Announce Type: cross Abstract: Large language models are increasingly deployed in applications that act on users' long-term behavior histories, from personal assistants to recommend

applicationsarxiv-cs-ai

Tutorials

VeriPIE: Checkable Query Plans and Evidence-Guided Selection for Text-to-SQL

arXiv:2610.17493v1 Announce Type: cross Abstract: Financial Artificial Intelligence (AI) governance and model risk management (MRM) emphasize independent validation, transparency, and effective challe

tutorialsarxiv-cs-ai

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

Vision: 'What Don't I Know About User's Preferences?' How Uncertainty Estimation Improves Proactive Assistant Alignment

arXiv:2610.15948v1 Announce Type: new Abstract: Proactive Smart Assistants (PSAs) increasingly use general knowledge, learned patterns from group-level data, patterns from individual user's data, and

safetyarxiv-cs-ai

VLRLA: Deployment-Time Adaptation of Vision-Language-Action Models through In-Context Reinforcement Learning

arXiv:2610.19517v1 Announce Type: cross Abstract: Vision-language-action (VLA) models connect visual perception and language understanding with robot control, providing a foundation for instruction-co

safetyarxiv-cs-ro

W-JEPA: Wavelet Joint-Embedding Predictive Architecture for Wearable Activity Recognition

arXiv:2610.19411v1 Announce Type: new Abstract: A major challenge in wearable device activity recognition is the heterogeneity across datasets in sensor placement, channel count, sampling rate and sub

researcharxiv-cs-lg

Weak Segmentation-Guided GAN for~Realistic Color Edition

arXiv:2610.16620v1 Announce Type: new Abstract: Editing the color of images in a realistic way finds many applications such as changing the perception of an image, data augmentation or film post proce

researcharxiv-cs-ai

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 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

When 1+1 Backfires: Rethinking Relevance-Diversity Balancing for Sample-Aware Visual Token Reduction

arXiv:2610.16615v1 Announce Type: new Abstract: Visual token compression has emerged as a critical technique for reducing the inference cost of Vision-Language Models. Existing methods select tokens b

When Goals Leak Across Relationships: How Cached Goal Representations Shape Cross-Client Decisions

arXiv:2610.17365v1 Announce Type: new Abstract: As LLM agents take on more autonomous roles, they may interact with multiple clients and counterparties whose goals and incentives conflict. If an agent

When Non-Adversarial Noise Hurts Learning: Benchmarking Skill Self-Evolution in Agents

model-releasesarxiv-cs-lg

arXiv:2610.19910v1 Announce Type: new Abstract: Large language model agents increasingly improve by distilling experience into reusable skills, but errors in that experience can persist in learned rul

Why Do VLMs Fail at Remote Physiological Measurement? Rethinking with Physiological Grounding and Numerical Alignment

model-releasesarxiv-cs-cv

arXiv:2610.19052v1 Announce Type: new Abstract: Video-based remote physiological measurement (RPM) has broad applications, while Vision-Language Models (VLMs) provide a promising opportunity to enable

Tutorials

Wong--Zakai Convergence and FNO Learning for Stochastic Volterra Equations

arXiv:2610.18939v1 Announce Type: cross Abstract: This paper studies Wong--Zakai convergence and Fourier neural operator learning for stochastic Volterra integral equations (SVIEs) describing random s

tutorialsarxiv-cs-lg

Applications

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

arXiv:2610.15625v1 Announce Type: new Abstract: World Action Models (WAMs) unify visual world modeling and action generation, yet their real-world deployment is heavily bottlenecked by iterative actio

applicationsarxiv-cs-cv

3DXTalker: Unifying Identity, Lip Sync, Emotion, and Spatial Dynamics in Expressive 3D Talking Avatars

arXiv:2602.10516v4 Announce Type: replace Abstract: Audio-driven 3D talking avatar generation is increasingly important in virtual communication, digital humans, and interactive media, where avatars m

researcharxiv-cs-cv

A Behavior-first approach to Multi-Intention Inverse Reinforcement Learning

arXiv:2602.07496v2 Announce Type: replace Abstract: Inverse Reinforcement Learning (IRL) seeks to infer reward functions from expert demonstrations. When demonstrations originate from multiple experts

researcharxiv-cs-lg

A Controlled Evaluation of Curvature Inspired Scalar Feature Scaling for Domain Generalization

arXiv:2610.18227v1 Announce Type: cross Abstract: Domain-specific curvature is an appealing idea for domain generalization (DG), but curvature learning can denote substantially different computations.

researcharxiv-cs-cv

A Gated Catchment Hydrology Model (GCHM) for Physically-Interpretable Rainfall-Evapotranspiration-Runoff Simulation Across Diverse Hydroclimatic Regimes

arXiv:2610.14493v1 Announce Type: new Abstract: Recent advances in machine learning have improved rainfall-runoff prediction, yet most data-driven models remain difficult to interpret and do not expli

agentsarxiv-cs-lg

A Nonlinear Time-Series Theory for Constant-step SGD with Momentum

model-releasesarxiv-cs-lg

arXiv:2610.16034v1 Announce Type: cross Abstract: Constant-step stochastic gradient descent with momentum (SGDM) augments the parameter recursion with a momentum state that carries geometrically decay

A physics-coupled graph neural operator for mid-plane six-component stress tensor field prediction in concrete penetration

arXiv:2610.16996v1 Announce Type: new Abstract: The penetration-resistant design of concrete structures requires the spatiotemporal evolution of the stress field within the target, whereas in design o

researcharxiv-cs-lg