Search: “safety”

Negative Self-Distillation: Learning to Reason by Avoiding Flaws

arXiv:2609.11699v1 Announce Type: new Abstract: On-Policy Self-Distillation (OPSD) has emerged as a popular paradigm for large language model (LLM) self-improvement, allowing models to act as their ow

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

ObstaDiff: Generalizable Diffusion Policy Learning via Obstacle-aware Representations

DGX agent

arXiv:2609.10918v1 Announce Type: cross Abstract: Imitation learning has achieved impressive results in robotic manipulation, yet most existing approaches assume clean backgrounds and lack explicit me

safetyarxiv-cs-lg

11 Sept 2026

On the Societal Impact of Machine Learning

arXiv:2510.23693v2 Announce Type: replace Abstract: This PhD thesis investigates the societal impact of machine learning (ML). ML increasingly informs consequential decisions and recommendations, sign

Order-Aware 2.5D Multiple Instance Learning for Preoperative MRI-Based Perineural Invasion Risk Assessment in Intrahepatic Cholangiocarcinoma

arXiv:2609.11271v1 Announce Type: new Abstract: Perineural invasion (PNI) is an adverse histopathologic marker in intrahepatic cholangiocarcinoma (ICC), but it is usually confirmed only after resectio

PEARL: A Task-Aware Framework for Evaluating Differentially Private Synthetic Educational Data

arXiv:2609.10612v1 Announce Type: cross Abstract: Personalized learning systems rely on real learner data, including performance, behavior, and demographic information, but these data are highly priva

Quantifying Logical Consistency in Transformers via Query-Key Alignment

arXiv:2502.17017v1 Announce Type: cross Abstract: Large language models (LLMs) have demonstrated impressive performance in various natural language processing tasks, yet their ability to perform multi

Reflex-Informed Neuromuscular Reinforcement Learning for Muscle-Driven Locomotion

arXiv:2609.11733v1 Announce Type: cross Abstract: Muscle-driven locomotion provides a physically grounded approach to generating realistic human movement. However, achieving both physiological plausib

Reinforcement Learning with Temporal-Logic-Based Causal Diagrams

arXiv:2306.13732v2 Announce Type: replace Abstract: We study a class of reinforcement learning (RL) tasks where the objective of the agent is to accomplish temporally extended goals. In this setting,

Rethinking Radiomap Blind Prediction with Limited Environment and Configuration Representations

arXiv:2609.11255v1 Announce Type: cross Abstract: Radiomap blind prediction infers radiomaps from observable representations of the propagation environment and base station (BS) configuration without

Risk-Averse Decision Making with Multi-Level Reliability Guarantees

arXiv:2609.11524v1 Announce Type: cross Abstract: Many applications in engineering, including wireless broadcasting, require designs that provide performance certificates at different target outage le

Scores Alone Do Not Prove Discovery: The Discovery Certification Protocol for Auditing AI Research Agents

arXiv:2609.09219v1 Announce Type: cross Abstract: AI research agents combine prior knowledge, public sources, and experimental feedback to produce useful results. The Discovery Certification Protocol

SEED-UMI: Sharing the Exoskeleton between human and robot for onE-to-one Dexterous demonstration

arXiv:2609.11753v1 Announce Type: new Abstract: Imitation learning for dexterous hands is bottlenecked by the difficulty of collecting contact-rich demonstrations that transfer faithfully to the robot

SenseNova-U1.5: Towards Native Unified Visual Intelligence

arXiv:2609.11929v1 Announce Type: new Abstract: We launch SenseNova-U1.5, an 8B-MoT native unified multimodal model that understands, reasons about, and generates visual content within an encoder-free

Sequence-Informed Geometric Evaluation of RNA 3D Structures

arXiv:2609.10644v1 Announce Type: cross Abstract: Computational RNA structure pipelines generate many candidate conformations for the same sequence. Reliable evaluation therefore requires more than re

SG-Blend: Learning an Interpolation Between Improved Swish and GELU for Robust Neural Representations

arXiv:2505.23942v2 Announce Type: replace Abstract: Prevailing activation functions such as Swish and GELU tend toward domain-specific optima, Swish was discovered via neural architecture search on vi

SIRF: A Spec-Internalized Risk Foundation Model for Industrial Content Risk Control

arXiv:2609.11752v1 Announce Type: cross Abstract: For industrial content risk control, the real deployment constraint is not average accuracy but how much risk can be auto-handled under high precision

Statistical analysis of Inverse Entropy-regularized Reinforcement Learning

arXiv:2512.06956v2 Announce Type: replace-cross Abstract: Inverse reinforcement learning aims to infer the reward function that explains expert behavior observed through trajectories of state--action

Streaming Translation and Transcription Through Speech-to-Text Causal Alignment

arXiv:2603.11578v2 Announce Type: replace Abstract: Simultaneous machine translation (SiMT) has traditionally relied on offline machine translation models coupled with human-engineered heuristics or l

Structural Process Supervision for Latent Chain-of-Thought Reasoning

arXiv:2609.09928v1 Announce Type: new Abstract: Latent reasoning approaches enhance token-level efficiency and robustness by replacing verbose, explicit chain-of-thought (CoT) tokens with compact cont

Target leakage, not model class, explains reported accuracy in survey-based cardiovascular screening: a leakage-tiered audit of glass-box and tabular foundation models

arXiv:2609.11838v1 Announce Type: new Abstract: Cardiovascular screening models trained on national health surveys routinely report areas under the receiver operating characteristic curve (AUROC) near

Testing Between the Test Cases: Proving End-to-End Steering in Conditions You Never Drove

arXiv:2609.10951v1 Announce Type: cross Abstract: AI-based automated vehicle testing is challenging because a model that passes every test condition can still fail in the real world. Formal verificati

The Eloquence submission for Task 2 of the Interspeech 2026 MLC-SLM challenge

arXiv:2609.11724v1 Announce Type: new Abstract: This paper details the Eloquence team's approach to Task 2 of the 2nd MLC-SLM challenge at Interspeech 2026, which involves multilingual Multiple-Choice

The Oligarch Barely Steers Model Collapse in Multi-Model Ecosystems

arXiv:2609.11146v1 Announce Type: cross Abstract: AI-generated text is flowing back into the training corpora of the next generation of models. Recursive training on it drives model collapse, and rece

UBCL: A Reinforcement Learning Framework for Controllable and Diverse Player Behaviors

arXiv:2512.10835v2 Announce Type: replace Abstract: This paper introduces a reinforcement learning framework that enables controllable and diverse player behaviors without relying on human gameplay da

Voice or Stereotype? Disentangling Acoustic and Content-Based Gender in Speech-to-Speech Models

arXiv:2609.09263v1 Announce Type: cross Abstract: Speech-to-speech (S2S) models now run inside dubbing, translation, and voice agents. Unlike text models, they hear the speaker's voice, which carries

When does a spectral prior help graph learning? Connectivity-loss estimation under road-network disruptions

arXiv:2609.11166v1 Announce Type: new Abstract: Rapid evaluation of many simultaneous road-link disruptions requires a practical compromise between exact spectral recomputation and local approximation

When More Is Not Better: Component Anti-Synergy in a P300 Speller

arXiv:2609.10961v1 Announce Type: new Abstract: P300 brain-computer interface (BCI) spellers can provide hands-free communication for people with severe motor impairments. Modern pipelines combine mul

When Noise Fabricates Bias: The Fragility of LLM-as-a-Judge Bias Measurement under Noisy Text

arXiv:2609.11067v1 Announce Type: new Abstract: Large language models are increasingly used as judges to measure social bias in text, yet the passages they judge are often noisy, containing typos, inf

Why Sample What You Can Enumerate? Exact Policy Optimization for Genomic Tool Selection

arXiv:2609.10221v2 Announce Type: new Abstract: Reinforcement learning over a frozen reasoner has become a common recipe for teaching a policy which external tools to invoke. We show that this recipe

Your Model Already Knows Don't Teach It, Learn to Ask It: Soft Prompting for Few-Shot Adaptation of Vision-Language Models

arXiv:2609.11310v1 Announce Type: new Abstract: We address few-shot object detection with vision-language models (VLMs) in out-of-domain settings such as aerial, industrial, and medical imagery, using

A Confidence-Aware Multimodal Fusion Framework for Industrial Human-Robot Collaboration

arXiv:2609.10339v1 Announce Type: new Abstract: A confidence-aware multimodal fusion framework (CAMF) is proposed to realize reliable human intention prediction for industrial human-robot collaboratio

A Farewell to the Bias-Variance Tradeoff? An Overview of the Theory of Overparameterized Machine Learning

arXiv:2109.02355v2 Announce Type: replace-cross Abstract: The last decade of progress in machine learning (ML), especially the deep learning era, has raised a number of scientific questions that chall

A statistical approach to bias in zero-shot learning: the lens of handwriting recognition

arXiv:2609.10084v1 Announce Type: cross Abstract: Generalized zero-shot learning (GZSL) has emerged as an important paradigm for visual recognition systems that must generalize to classes that were no

A Unifying Perspective on Probabilities as Model Predictions

arXiv:2609.09855v1 Announce Type: cross Abstract: Although probabilistic statements are ubiquitous, foundational disagreements persist about their understanding, as exemplified by debates between Baye

Actuator Dynamics Curricula for Narrow-Viability Tasks in Legged Robot Learning

arXiv:2609.09492v1 Announce Type: new Abstract: Reinforcement learning has produced capable controllers across a broad range of legged-robot tasks, but a subset of these tasks fail to converge under s

Advanced Brain Tissue Imaging with Data-Consistent Diffusion Priors in Laminographic X-Ray Nanoimaging

arXiv:2609.10456v1 Announce Type: new Abstract: Nanoscale imaging of mammalian brains is critical for connectomics. X-ray laminography enables high-throughput imaging of extended, plate-like biologica

AgentBrew: Offline Tool-Use Agent Learning from Raw Real-World Trajectories

arXiv:2609.05837v1 Announce Type: new Abstract: LLM-based agents are increasingly deployed in real-world applications through tool-use APIs, yet training them for specific environments remains fundame

AgenticGen: Reward-Guided Agentic Video Generation for Advertising

arXiv:2609.09187v1 Announce Type: cross Abstract: Advertising video generation is not only a video synthesis task, but also a product-conditioned reasoning problem whose success is measured by online

An Auditable Symbolic-RAG-Generative AI Architecture for Goal-Oriented Conversation Orchestration

arXiv:2609.07152v1 Announce Type: new Abstract: Goal-oriented conversational systems must answer factual questions, understand visitor-provided information, and advance business objectives without bec

Applying foundation model embeddings towards urban livability evaluation

arXiv:2609.09429v1 Announce Type: new Abstract: While accurate measurement of socioeconomic indicators remains challenging in data-scarce regions, which limits policy interventions and resource alloca

Are You Learning Biological Signal or Shortcuts? Auditing and Mitigating Bias in Protein-Protein Interaction Datasets

arXiv:2609.10193v1 Announce Type: cross Abstract: Protein-protein interaction (PPI) databases do not faithfully reflect biological realities. Instead, they are influenced by study and technical biases

AXON: A ROS 2 RMW with Shared-Memory/QUIC Transport and QKD/ML-KEM Key Establishment

arXiv:2609.10024v1 Announce Type: new Abstract: Robot Operating System 2 (ROS 2) standardizes application code against a middleware interface (RMW) whose reference implementations are built on the Dat

Belief-State Engine: Augmenting LLMs for Principled Planning Under Partial Observability

arXiv:2609.10036v1 Announce Type: cross Abstract: Large language model agents produce fluent action sequences across a wide range of tasks, yet they fail in characteristic ways once the environment be

BETA-Labeling for Multilingual Dataset Construction in Low-Resource IR

arXiv:2602.14488v3 Announce Type: replace-cross Abstract: IR in low-resource languages remains limited by the scarcity of high-quality, task-specific annotated datasets. Manual annotation is expensive

Beyond Retrieval: Joint Supervision and Multimodal Document Ranking for Textbook Question Answering

arXiv:2505.13520v2 Announce Type: replace-cross Abstract: Textbook question answering (TQA) is a complex task, requiring the interpretation of complex multimodal context. Although recent advances have

Beyond Right and Wrong: Evaluating Second-order Social Reasoning in Large Language Models

arXiv:2609.05437v1 Announce Type: new Abstract: Previous AI alignment efforts have focused primarily on first-order social norms -- teaching models what is socially acceptable or unacceptable (e.g., `

BRACE: Anchored Bellman-Residual Correction for Stale Critics in Asynchronous RL

arXiv:2609.09783v1 Announce Type: new Abstract: Asynchronous reinforcement learning has become the standard way to scale training for language models, but the resulting policy lag biases the critic to

Bridging the Semantic-Utility Gap in Multimodal RAG via Generator-in-the-Loop Alignment

arXiv:2609.08188v1 Announce Type: new Abstract: Vision-language models (VLMs) augmented with retrieval-augmented generation (RAG) benefit from access to external evidence. However, standard retrievers