Search: “context”

CHILLGuard: Towards Fine-Grained Chinese LLM Safety Guardrail with Scalable Data Construction and Model-aware Preference Alignment

arXiv:2606.15396v2 Announce Type: replace-cross Abstract: Malicious content generated from large language models (LLMs) could pose severe safety risks and ethical concerns. While existing LLM safety g

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Model Releases

CHORDONOMICON: A Dataset of 666,000 Songs and their Chord Progressions

DGX agent

arXiv:2410.22046v4 Announce Type: replace-cross Abstract: Chord progressions encapsulate important information about music, pertaining to its structure and conveyed emotions. They serve as the backbon

model-releasesarxiv-cs-lg

2 Oct 2026

CoEvolve: Construct-to-Edit Visual Grounding with Bidirectional State Refinement

arXiv:2610.01710v1 Announce Type: new Abstract: Visual grounding localizes an object described by language with a bounding box. Most multimodal grounding models compress target identification, spatial

researcharxiv-cs-ai

Conflicting Supervision Moves Commitment, Not Capability: A 12.29{sigma} arrangement effect that is exactly zero under a convention-agnostic score

arXiv:2610.00234v1 Announce Type: new Abstract: 'Train a model on the same problems written under two incompatible conventions, both correct, and ask what the ordering of that data writes into the par

Constant-Memory Recall: Learned Associations in a Fixed Matrix State

model-releasesarxiv-cs-lg

arXiv:2610.00232v1 Announce Type: new Abstract: Fixed-size recurrent memory limits storage growth during inference, but successful recall depends on the task and training. We study a small DeltaNet va

Cross-Lingual Alignment for Decoder-Only Models using MoE Routers

arXiv:2610.01921v1 Announce Type: cross Abstract: Cross-lingual contrastive learning has been a core component of multilingual encoder training, but the ability to explicitly align representations is

safetyarxiv-cs-ai

Decision Titan: Test-Time Training for Long-Term Memory in Offline Reinforcement Learning

arXiv:2610.01513v1 Announce Type: new Abstract: Long-term dependencies remain a major challenge for sequential decision-making in the field of AI: RNNs suffer from vanishing gradients and the limited

DeFA: Dependency-Guided Failure Attribution for LLM Agents

arXiv:2610.01256v1 Announce Type: new Abstract: Errors in LLM agent executions and their visible consequences can be separated by many steps, making decisive-error localization a matter of understandi

agentsarxiv-cs-ai

Detect, Explain, Interpret: An End-to-End Benchmark for Time Series Anomaly Detection, Explainability and Interpretability

arXiv:2610.01168v1 Announce Type: cross Abstract: Time Series Anomaly Detection has received increasing attention, driven by the growing availability of complex time series data. This surge has led to

Detecting Inconsistencies in Model Specifications with LLM-as-Verifier Reasoning

arXiv:2610.01847v1 Announce Type: cross Abstract: Model specifications define how large language models (LLMs) should behave, guiding alignment training, inference-time behavior, and evaluation. Yet t

safetyarxiv-cs-ai

Divide-and-Remember: Recursive Action-Relevant Memory for Long-Horizon VLA Policies

arXiv:2610.00982v1 Announce Type: cross Abstract: Vision-language-action (VLA) models struggle on history-dependent manipulation tasks, where the current observation alone does not determine the actio

End-to-End Learning vs. Modular Architectures: Comparative Insights into Autonomous Driving Systems

arXiv:2610.01746v1 Announce Type: cross Abstract: Autonomous driving systems have become a central focus of intelligent transportation research, with End-to-End Learning and Modular Architectures offe

safetyarxiv-cs-cv

Tutorials

Exploring More, Reasoning Better: Stepwise Risk-Sensitive GRPO for Diffusion Language Models

arXiv:2610.00661v1 Announce Type: cross Abstract: Diffusion large language models (dLLMs) generate text by denoising a sequence or successive blocks, allowing several tokens to be revealed in parallel

tutorialsarxiv-cs-ai

EyeTAG: Eye Trajectory-Aware Gaze Estimation

arXiv:2610.00922v1 Announce Type: new Abstract: Gaze estimation under natural head-eye motion underpins applications from driver monitoring to human-computer interaction. Single-frame methods predict

safetyarxiv-cs-cv

FAME: Force-Adaptive RL for Expanding the Manipulation Envelope of a Full-Scale Humanoid

arXiv:2603.08961v2 Announce Type: replace Abstract: Maintaining balance under external hand forces is critical for humanoid bimanual manipulation, where interaction forces propagate through the kinema

safetyarxiv-cs-ro

Hardware

FastCI: Efficient GPU-Intensive CI for LLM Training Frameworks

arXiv:2610.01967v1 Announce Type: new Abstract: As large language models (LLMs) keep growing in size and complexity, their training frameworks evolve at a rapid pace as well. Therefore, continuous int

hardwarearxiv-cs-lg

Applications

Fusing Visual and Textual Representations via Multi-layer Fusing Transformers for Vietnamese Visual Question Answering

arXiv:2610.01637v1 Announce Type: new Abstract: In recent decades, artificial intelligence has made significant progress in understanding and interacting with images. One of the important applications

applicationsarxiv-cs-cv

G2-Nav: Grounded and Guarded Vision-Language Costmaps for Robot Social Navigation

arXiv:2607.16956v2 Announce Type: replace Abstract: Social navigation requires the robot to reason and respond in complex real-world environments. While recent works attempt to incorporate human-level

safetyarxiv-cs-ro

GenGait: A Transformer-Based Model for Human Gait Anomaly Detection and Normative Twin Generation

arXiv:2604.01997v2 Announce Type: replace Abstract: Gait analysis provides an objective characterization of locomotor function and is widely used to support diagnosis and rehabilitation monitoring acr

researcharxiv-cs-ai

Global Coherence: When Every Agent Is Right and the Team Is Still Wrong - A Local-to-Global Semantic Foundation for Multi-Agent Collaboration

arXiv:2610.02036v1 Announce Type: new Abstract: AI agents can each make locally valid decisions yet jointly produce an invalid result. We call this the global coherence problem: a failure of shared st

Heavy-Tailed Memory Traces in Long-Horizon Language Agents

arXiv:2610.00010v1 Announce Type: new Abstract: Long-horizon language agents increasingly rely on external memory as a frozen world model, yet current memory systems are usually judged only by task su

safetyarxiv-cs-ai

Hierarchical Continuous Diffusion Language Models

arXiv:2610.02193v1 Announce Type: cross Abstract: Discrete diffusion language models offer a compelling alternative to autoregressive generation for tasks demanding bidirectional reasoning and global

researcharxiv-cs-ai

Higher-Order Molecular Grammars for Generative and Foundation Models in Chemistry

arXiv:2610.02186v1 Announce Type: cross Abstract: Molecular learning models are strongly shaped by their underlying representations. Yet standard sequential and graph formalisms struggle to explicitly

How Far is Adam from Natural Gradient Descent?

arXiv:2610.00004v1 Announce Type: new Abstract: Adam is the standard optimizer in deep learning, yet its geometric relationship to natural gradient descent (NGD) contains unresolved questions. We stud

Increasing Width Allows Greedy Layer-wise Training to Rival End-to-End Backpropagation in Self-Supervised Learning

arXiv:2610.00753v1 Announce Type: cross Abstract: End-to-end backpropagation has been the dominant mode of training in deep learning, allowing for the coordination of parameter updates across layers o

Local Ai

IndoorBEV: A Lightweight Real-Time LiDAR BEV Perception System for Indoor Mobile Robots

arXiv:2610.00355v1 Announce Type: new Abstract: Efficient indoor LiDAR perception is challenging because mobile robots must understand cluttered three-dimensional environments under strict latency and

local-aiarxiv-cs-ro

InterEvolve: Test-Time Evolution of Reward Programs for Humanoid Loco-Manipulation

arXiv:2610.02196v1 Announce Type: cross Abstract: We study test-time evolution for humanoid loco-manipulation: solving tasks that a controller was never trained for by repurposing its existing skills,

agentsarxiv-cs-cv

Industry

It is here now ! Enjoy our 4B model 🐸 https://huggingface.co/microsoft/FrogNano-4B-2609

It is here now ! Enjoy our 4B model 🐸 https://huggingface.co/microsoft/FrogNano-4B-2609 4B parameters. ZERO distillation. 61.5% on SWE-bench Verified 🤯 Meet FrogNano 🐸: Qwen3.5-4B post-trained purely

industryclem-delangue--x

JevSpawn: Adaptive Agentic Inference through Compositional Action Spaces

arXiv:2610.00437v1 Announce Type: new Abstract: LLM agents generate intermediate reasoning and actions token by token, making extended interactions slow and computationally expensive. Jev-style models

JoinGR: Learning to Traverse Join Graphs for Table Retrieval

arXiv:2610.01064v1 Announce Type: cross Abstract: Retrieving the right tables is a prerequisite for Text-to-SQL over realistic databases. Dense table retrievers rank schema elements independently, but

Learning Rate Transfer for Hybrid Transformer-SSM Architectures

model-releasesarxiv-cs-lg

arXiv:2610.01172v1 Announce Type: new Abstract: We study learning rate (LR) scaling for hybrid architectures combining Transformer and State-Space Model (SSM) blocks, a class adopted by several recent

Tutorials

Learning to Ask: Information Acquisition for SLM-LLM Collaboration, under a budget

arXiv:2610.01236v1 Announce Type: new Abstract: Collaboration between a small language model (SLM) and a large language model (LLM) offers an opportunity to combine the efficiency of smaller models wi

tutorialsarxiv-cs-ai

Localizing Transfer Between Memorization Tasks

arXiv:2610.00771v1 Announce Type: new Abstract: A central puzzle in transfer learning is why pre-training on one task can accelerate training or improve performance on another task, and what mechanism

Low-Budget Active Learning through Entropic Optimal Transport

arXiv:2610.01199v1 Announce Type: new Abstract: We consider low-budget active learning, which consists of selecting a limited number of points, the coreset, such that a model can be trained to high ac

MapLightning: Online Vectorized HD Map Construction with 1D Map Tokens

model-releasesarxiv-cs-cv

arXiv:2610.01905v1 Announce Type: new Abstract: Online vectorized HD map construction is essential for scaling safe autonomous driving and requires accurate, real-time inference. Prior methods typical

MCIR: A Feature Dependence-Aware Explainability Method with Reliability Guarantees

arXiv:2610.01641v1 Announce Type: cross Abstract: Modern machine-learning models often contain strongly dependent or redundant features, making feature attribution difficult because shared predictive

Measuring the Microtask Eligibility Gap: When Is an Off-the-Shelf SLM Enough for an Agent Harness?

arXiv:2610.00025v1 Announce Type: new Abstract: Agent harnesses increasingly want to run small language models (SLMs) on the microtasks around a frontier large language model (LLM) planner: auto-appro

MemFit: Efficient Long-Term Agentic Memory

arXiv:2610.00872v1 Announce Type: new Abstract: Long-term memory systems for large language models (LLMs) have gained popularity for extending reasoning capabilities across applications. Current memor

agentsarxiv-cs-ai

MIKASA-Robo-VLA: Benchmarking Memory in VLA Models for Long-Horizon Manipulation

arXiv:2610.00604v1 Announce Type: cross Abstract: Vision-language-action policies often see only one or a few recent frames, which makes it difficult to evaluate how they use information that disappea

Mimir: Physics-Grounded LLM Agents for Long-Horizon Irrigation Control

arXiv:2610.02038v1 Announce Type: new Abstract: Large language model (LLM) agents increasingly combine reasoning, tool use, and action, but most evidence comes from episodic tasks with relatively imme

agentsarxiv-cs-ai

Mingbird: A Local-First Agent Harness Enabling Small Open Models to Complete Real Tasks

arXiv:2610.02001v1 Announce Type: new Abstract: Small open-weight models (2-9B) run on ordinary laptops, but under cloud-scale agent harnesses they rarely complete real tasks: tool prefill overflows t

MOVE: Multimodal Open-world Verification and Expansion for Graph Learning

arXiv:2610.00268v1 Announce Type: new Abstract: Multimodal graph learning faces a fundamental challenge: new classes may emerge after deployment, while models are trained with a fixed label space. Exi

One pool, many targets: a conservation layer and what archival data can identify

model-releasesarxiv-cs-lg

arXiv:2610.00445v1 Announce Type: new Abstract: Pairwise guide--transcript scores do not enforce conservation of a finite guide-loaded RISC pool when they are interpreted independently as occupancies.

Local Ai

OneStreamer: Unifying Perception, Memory, and Proactive Response in Streaming Video Interaction

arXiv:2610.01762v1 Announce Type: new Abstract: Streaming video LLMs must retain evidence before its relevance to future tasks is known and respond when sufficient evidence becomes available. The chal

local-aiarxiv-cs-cv

Online Planning for Sparse Ground Target Search from a High-Altitude UAV under Partial Observability

arXiv:2610.01067v1 Announce Type: new Abstract: Unmanned aerial vehicles (UAVs) searching for ground targets from a high altitude face a unique challenge, particularly when the target is already withi

agentsarxiv-cs-ro

PACE: Persona Adaptation through Conversational Elicitation in Human-Robot Interaction

arXiv:2607.15579v3 Announce Type: replace Abstract: Equipping humanoid robots with coherent and adaptable personas is crucial for fostering natural, engaging, and trustworthy human-robot interaction (

researcharxiv-cs-ro

Permutation-Robust Decision Modeling with Candidate-Independent Block-Causal Attention

arXiv:2610.01601v1 Announce Type: cross Abstract: Decision models often score a variable-sized set of candidate actions encoded in a single sequence. This setting is increasingly relevant for System 1

Personalized Image Generation with Reasoning and Reflection

arXiv:2610.00737v1 Announce Type: cross Abstract: Personalized image generation has remained narrowly focused on conditional synthesis from curated visual exemplars, rather than capturing who a user i