Search: “llm”

MindFlow: Mind Supernet Powered Thinking Flows for Research Idea Innovation

arXiv:2610.11966v1 Announce Type: new Abstract: Research idea innovation is a fundamental engine of scientific progress, yet it remains difficult to generate and evaluate in a scalable and controllabl

agentsarxiv-cs-ai

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One Skill Too Many: How Co-Installed Skills Conflict in Coding Agents

DGX agent

arXiv:2610.11647v1 Announce Type: cross Abstract: Coding agents are extended with agent skills, directories whose SKILL.md tells the model when and how to perform a task. Because skills come from inde

agentsarxiv-cs-ai

9 Oct 2026

Optimal Transport Depth Up-Scaling

arXiv:2508.08011v2 Announce Type: replace Abstract: Pre-training Large Language Models (LLMs) from scratch at larger scales yields remarkable performance but incurs substantially high training costs.

Perceptually Grounded and Semantics-Aware Evaluation for Holistic Co-Speech Gesture Generation

model-releasesarxiv-cs-cv

arXiv:2610.11669v1 Announce Type: new Abstract: Holistic and semantics-aware co-speech gesture generation has advanced rapidly, yet evaluation remains behind: objective metrics do not consistently ref

Prompts versus Rules: Auditing and Controlling Speech Naturalness Behaviors in Voice User Simulators

arXiv:2610.11015v1 Announce Type: new Abstract: As voice agents gain more popularity commercially, the user simulators used to evaluate the deployed agents are also being developed to include more rea

agentsarxiv-cs-cl

REMORY: Learning Residual Memory for Context Compaction

arXiv:2610.11287v1 Announce Type: cross Abstract: Long-horizon agents compact their history to continue within a finite context window, but a textual summary alone may not support every subsequent dec

Rethinking Contrastive Loss in CLIP Post-training: A Complementary Framework with Frozen Text Encoder

arXiv:2610.11374v1 Announce Type: cross Abstract: CLIP serves as a foundational vision-language model and the de facto vision encoder for downstream VLMs such as LLaVA. Post-training offers a lightwei

researcharxiv-cs-ai

RISR: Residual-Informed Scientific Equation Discovery with Large Language Models

arXiv:2610.11387v1 Announce Type: cross Abstract: Symbolic regression combines structural search with numerical fitting, but aggregate fit scores do not describe how the remaining error varies across

tutorialsarxiv-cs-ai

Safe, Persistent, and Evolving Agent Harness for Understanding Partially Observable Worlds

arXiv:2610.11552v1 Announce Type: new Abstract: Large language model agents can invoke tools fluently, but enterprise workflows demand more than selecting the right tools: actions must strictly comply

Sera: Semantic Representation Aggregation for Reliable and Interpretable Battery Health Forecasting

arXiv:2610.11567v1 Announce Type: cross Abstract: Battery state of health (SoH) forecasting is important for battery management, but remains challenging due to nonlinear degradation and heterogeneity

SFT-as-Context Mitigates Forgetting in Supervised Fine-Tuning

arXiv:2610.11132v1 Announce Type: cross Abstract: Supervised fine-tuning (SFT) equips large language models (LLMs) with specialized capabilities, but often comes at the cost of forgetting the general

researcharxiv-cs-ai

SignRAG: Unified Retrieval-Augmented Gloss-Free Sign Language Translation

model-releasesarxiv-cs-cl

arXiv:2610.11371v1 Announce Type: new Abstract: Contemporary decoder-only large language models (LLMs) have demonstrated strong capabilities across a wide range of domains. However, existing pretraini

Skill-SLM: Agent Skill-driven Small Language Models for Reliable Robot Operation

arXiv:2610.10812v1 Announce Type: new Abstract: Small language models (SLMs) have been increasingly adopted for onboard robot operation because they enable intelligent decision-making. However, existi

agentsarxiv-cs-ro

Sparse Attention Is Matrix Approximation, Not Choosing from a Bag of Values

arXiv:2610.10871v1 Announce Type: new Abstract: Large Language Models (LLMs) achieve strong performance across many domains, but their efficiency is limited by the quadratic cost of attention with res

Spectral Weight Decay: Inducing Low-Rank Structure in Neural Network Weights

model-releasesarxiv-cs-lg

arXiv:2610.11730v1 Announce Type: new Abstract: Standard weight decay treats each weight matrix as a vector and ignores its spectral structure. We introduce spectral weight decay, a post-step decouple

Stop Probing, Start Coding: Why Linear Probes and Sparse Autoencoders Fail at Compositional Generalisation

model-releasesarxiv-cs-lg

arXiv:2603.28744v2 Announce Type: replace Abstract: The linear representation hypothesis states that neural network activations encode high-level concepts as linear mixtures. However, under superposit

Synthesis Through Simulation: Generating Coherent Enterprise Data via Scalable Agent-System Interaction

arXiv:2610.10549v1 Announce Type: new Abstract: Tool-calling agents have become central to enterprise AI, yet training and evaluating them at scale remains severely constrained due to business and leg

safetyarxiv-cs-ai

The '10th Juror': Open-Set Standpoint Screening for Bureaucratic Bias Detection

arXiv:2610.11136v1 Announce Type: new Abstract: Presupposing the boundaries of bias is itself a form of bias. We study closed-loop bias governance for Dutch government documents, where a system must d

local-aiarxiv-cs-cl

USDCraft: Geometrically Grounded Programmatic Modeling of Articulated 3D Assets for Simulation

arXiv:2610.11322v1 Announce Type: new Abstract: Geometrically faithful and functional articulated 3D assets are essential for real-to-sim robot manipulation, where policies trained in simulation must

tutorialsarxiv-cs-ro

When Interfaces Speak: Data-Aware Generative UI Harness for Active Interaction

arXiv:2610.11123v1 Announce Type: new Abstract: Most human-agent interaction today remains text-based. Natural language can impose cognitive overload, ambiguity, information chaos, and slow input for

When Scene Text Hijacks the Scene: Uncovering, Exploiting, and Mitigating Rendered-Text Semantic Leakage in Image Generation Models

arXiv:2610.11286v1 Announce Type: new Abstract: The reliability and accountability of image generative models (IGMs) are essential for building responsible and trustworthy AI systems. Recent IGMs, suc

local-aiarxiv-cs-cv

Adaptive Code Generation for Controlling Robots

arXiv:2610.09588v1 Announce Type: new Abstract: Deploying robots as Complex Adaptive Systems (CAS) in unknown and dynamic environments necessitates a transition from rigid command libraries toward int

researcharxiv-cs-ro

AeroEval: Staged Program and Execution Validation for AI-Generated Drone Missions

arXiv:2610.09764v1 Announce Type: new Abstract: Large Language Models (LLMs) can generate drone programs from natural-language mission descriptions, but syntactically valid programs may still violate

local-aiarxiv-cs-ro

An Empirical Study of Agent Skills' Downstream Utility

arXiv:2610.08875v1 Announce Type: cross Abstract: Agent Skills package procedural guidance and resources for reuse, but a relevant Skill does not necessarily improve task performance. Existing studies

agentsarxiv-cs-lg

Attention via Black-Box Vector Search

arXiv:2610.10135v1 Announce Type: cross Abstract: Sparse attention mechanisms estimate attention over n tokens using a small subset of keys. Many existing approaches use maximum inner product search (

researcharxiv-cs-lg

Batch Augmentation with Unimodal Fine-tuning for Multimodal Fusion of Large Language Models

arXiv:2505.06592v2 Announce Type: replace Abstract: In this paper, we propose batch augmentation with unimodal fine-tuning for multimodal learning. We start with pre-trained unimodal models. We fine-t

researcharxiv-cs-cv

Bookkeeping, Composition, or Unreachable Gold? Reading MemoryAgentBench's Conflict-Resolution Scores Against a Frozen Last-Write Resolver

model-releasesarxiv-cs-cl

arXiv:2610.09193v1 Announce Type: cross Abstract: MemoryAgentBench's Conflict Resolution split is read as measuring 'selective forgetting'. We execute the benchmark's own rule - the newest statement a

CATune: Structural Constraint-Aware Bayesian Optimization for DBMS Configuration Tuning

arXiv:2610.09276v1 Announce Type: cross Abstract: Modern DBMSs expose hundreds of configuration knobs, resulting in a high-dimensional and heterogeneous search space that makes automated tuning costly

researcharxiv-cs-lg

CIRRA: Dual-Level Continual Instruction Reconciliation with Ongoing Execution for Embodied Robot Agents in Interactive Household Tasks

model-releasesarxiv-cs-cv

arXiv:2610.08862v1 Announce Type: cross Abstract: Household robots must accommodate new user instructions while executing ongoing tasks. Existing agents often regenerate or extensively revise the rema

CoTrace: Data Recipes for Training Terminal Agents with Harness-Model Co-Evolution

arXiv:2610.10426v1 Announce Type: new Abstract: Terminal-agent capability depends jointly on model weights and the runtime harness that formats prompts, binds tools, and handles error recovery. Existi

Dialect-Robust Speech Language Models with Synthetic Pseudo-Dialect Augmentation

arXiv:2610.09321v1 Announce Type: new Abstract: Speech Language Model (SLM) performance often degrades on dialects due to data scarcity. Conventional text-to-speech (TTS) augmentation struggles to cov

FedSSMCoOp: SSM Encoders for light-weight Federated Prompt Learning for Few-shot Classification

arXiv:2610.09907v1 Announce Type: new Abstract: Vision-Language Models (VLMs) have shown strong performance across a wide range of downstream vision tasks, thanks to the complementary information cont

safetyarxiv-cs-cv

Generative AI for Autonomous Driving: Frontiers and Opportunities

arXiv:2505.08854v2 Announce Type: replace Abstract: Generative Artificial Intelligence (GenAI) constitutes a transformative technological wave that reconfigures industries through its unparalleled cap

safetyarxiv-cs-cv

IVG-UAV: An Intelligent Voice-Guided UAV System for Autonomous Ripe Fruit Harvesting with Vision-Based Classification and Adaptive Path Planning

arXiv:2610.09398v1 Announce Type: new Abstract: In tropical regions, their agricultural sectors remain highly dependent on manual labor for fruit harvesting. On large-scale farms, this dependency ofte

agentsarxiv-cs-ro

Kernel Autoresearch for Open-Ended Model Discovery

arXiv:2610.10394v1 Announce Type: new Abstract: Kernels encode the inductive bias of a wide range of machine learning models, yet automated kernel design faces a fundamental dilemma. A fixed grammar o

safetyarxiv-cs-lg

Mechanics of Long-Context Hybrid Models Part 1.1: From Hybrid Attention to Hybrid Position

arXiv:2610.10114v1 Announce Type: new Abstract: The architectural design of Large Language Models (LLMs) is shifting from traditional full-attention-only models to hybrid models, which combine differe

tutorialsarxiv-cs-cl

Multi-Objective Aligned Small Language Model Framework for SUD Patient Dialogue Generation

arXiv:2610.09209v1 Announce Type: new Abstract: Substance Use Disorder (SUD) counseling requires patient responses that reflect underlying cognitive states such as beliefs, coping strategies, and read

OrBIT: Structure-Guided Embedding Compression

arXiv:2610.10385v1 Announce Type: new Abstract: Embedding tables are among the largest components of modern language models. Most compression methods fix a coding geometry such as coordinate blocks, l

local-aiarxiv-cs-lg

Prototype-Based Knowledge Guidance for Fine-Grained Structured Radiology Reporting

model-releasesarxiv-cs-cv

arXiv:2603.11938v2 Announce Type: replace-cross Abstract: Structured radiology reporting promises faster, more consistent communication than free text, but automation remains difficult as models must

Quantize by Drift: Label-Free Mixed-Precision Post-Training Quantization for Text Embedders

arXiv:2610.09227v1 Announce Type: cross Abstract: Mixed-precision post-training quantization needs a per-module sensitivity signal; for a text embedder the obvious one -- the retrieval quality a modul

Robotic Ultra-Long-Horizon Manipulation Skills via Human-guided Lifelong Code Generation

arXiv:2509.18597v3 Announce Type: replace Abstract: Large language models (LLMs) can translate natural-language instructions for robotic manipulation into executable code, but ambiguity, noisy generat

tutorialsarxiv-cs-ro

SAPD: Step-Aligned Privileged Distillation

arXiv:2610.09665v1 Announce Type: new Abstract: On-policy post-training can improve large language models by learning from their own trajectories, but requires costly rollout generation. We ask whethe

Steering Follows Geometry, Not Labels: Emotion Directions in a Full-Duplex Speech Model

arXiv:2610.08887v1 Announce Type: new Abstract: Full-duplex voice agents need to modulate emotion and delivery during real-time conversations, when de-escalating a complaint, carrying urgency in dispa

Validity Without Ground Truth: What Stated-Preference Economics Offers the Evaluation of Language Models

arXiv:2610.10506v1 Announce Type: cross Abstract: Many of the questions now put to large language models have no correct answer to score against: what a policy is worth, which option a user should cho

A Systematic Study of Small Language Models on Abstract Reasoning Tasks

model-releasesarxiv-cs-cl

arXiv:2610.08680v1 Announce Type: cross Abstract: Endpoint accuracy on abstract-reasoning benchmarks does not reveal whether a language model has acquired a transferable rule or fit distribution-speci

Adaptive Model Inversion Attacks Generalize a Privacy-Robustness Tradeoff

arXiv:2610.07677v1 Announce Type: new Abstract: In this paper, we show that standard evaluations of high-resolution Model Inversion Attacks (MIAs) significantly underestimate training-data privacy lea

researcharxiv-cs-lg

Hardware

AEGIS: Runtime-Guided GPU Collocation for Multi-Tenant Deep Learning Training

arXiv:2508.19073v4 Announce Type: replace-cross Abstract: Deep learning training commonly runs on shared multi-tenant GPU servers, where exclusive allocation provides isolation but can leave resources

hardwarearxiv-cs-lg

Can Semantic Geometry Teach an AI Judgement?

arXiv:2610.07249v1 Announce Type: new Abstract: How can an AI agent determine what rules to follow? One rule permits an action. Another imposes a condition, exception, or conflicting obligation. Deter

safetyarxiv-cs-ai