Hugging Face Trending Papers
Jun 8
Context-Fractured Decomposition Attacks on Tool-Using LLM Agents: Exploiting Artifact Provenance Gaps
Tool-using LLM agents interact with the world through actions that persist state in artifacts (e. g.
Benchmarks and evaluation
Leaderboards, eval harnesses and ablations — the contested business of deciding which model is actually better.
arXiv AI
Jun 8
CrowdMath: A Dataset of Crowdsourced Mathematical Research Discussions
arXiv:2606. 06526v1 Announce Type: new Abstract: Large language models have made substantial progress on mathematical reasoning, but existing benchmarks typically evaluate well-specified problems with final answers, step-by-step solutions, or complete proofs.
arXiv AI
Jun 8
Think Fast: Estimating No-CoT Task-Completion Time Horizons of Frontier AI Models
arXiv:2606. 07157v1 Announce Type: new Abstract: Many efforts to ensure frontier AI models are safe rely on monitoring their chain-of-thought (CoT) reasoning.
arXiv AI
Jun 8
REMEDI: A Benchmark for Retention and Unlearning Evaluation in Multi-label Clinical Disease Inference
arXiv:2606. 07141v1 Announce Type: cross Abstract: Language models trained for clinical disease inference are trained on patient data, which may include sensitive and private information, and data owners may request the removal of their data from a trained model due to privacy or copyright concerns.
arXiv AI
Jun 8
Multi-Agent Reasoning with Consistency Verification Improves Uncertainty Calibration in Medical MCQA
arXiv:2603. 24481v2 Announce Type: replace Abstract: Miscalibrated confidence scores are a practical obstacle to deploying AI in clinical settings.
arXiv Machine Learning
Jun 8
On the Effect of Neural Field Reparameterization for 4DVAR
arXiv:2509. 21751v2 Announce Type: replace Abstract: Four-dimensional variational data assimilation (4DVAR) is a cornerstone of numerical weather prediction, yet it remains computationally intensive and sensitive to initialization due to the non-convexity of its objective function.
arXiv AI
Jun 8
CHDP: Cooperative Hybrid Diffusion Policies for Reinforcement Learning in Parameterized Action Space
arXiv:2601. 05675v2 Announce Type: replace Abstract: Hybrid action space, which combines discrete choices and continuous parameters, is prevalent in domains such as robot control and game AI.
arXiv Machine Learning
Jun 8
Chunking the Critic: A Transformer-based Soft Actor-Critic with N-Step Returns
arXiv:2503. 03660v4 Announce Type: replace Abstract: We introduce a sequence-conditioned critic for Soft Actor-Critic (SAC) that models trajectory context with a lightweight Transformer and trains on aggregated $N$-step targets.
arXiv AI
Jun 8
Hierarchical Certified Semantic Commitment for Byzantine-Resilient LLM-Agent Collaboration
arXiv:2606. 07316v1 Announce Type: cross Abstract: Byzantine collaboration among large-language-model agents requires a finality-control primitive: given delivered stochastic, structured natural-language proposals, the protocol must decide whether the round supports a commit, what kind of commit, or a typed safe abort.
arXiv AI
Jun 8
MCERF: Advancing Multimodal LLM Evaluation of Engineering Documentation with Enhanced Retrieval
arXiv:2604. 09552v2 Announce Type: replace-cross Abstract: Engineering rulebooks and technical standards contain multimodal information like dense text, tables, and illustrations that are challenging for retrieval augmented generation (RAG) systems.
arXiv AI
Jun 8
COF26: A new on-top functional for multiconfiguration pair-density functional theory
arXiv:2605. 06215v2 Announce Type: replace-cross Abstract: Multiconfiguration pair-density functional theory (MC-PDFT) provides an efficient and accurate framework for computing electronic energies in strongly correlated molecular systems, with the quality of the on-top functional being a key determinant of its predictive accuracy.
arXiv AI
Jun 8
Acoustic Cue Alignment in Audio Language Models for Speech Emotion Recognition
arXiv:2606. 07309v1 Announce Type: cross Abstract: Instruction-following audio language models (ALMs) can be augmented with explicit acoustic cues, yet it remains unclear whether such cues are used in a grounded way when the raw audio is already available.
arXiv Machine Learning
Jun 8
TorchKM: A GPU-Oriented Library for Kernel Learning and Model Selection
arXiv:2606. 06742v1 Announce Type: new Abstract: TorchKM is an open-source library for kernel machines, including support vector machines, kernel logistic regression, and kernel quantile regression, with GPU acceleration.
arXiv AI
Jun 8
Graph Neural Network leveraging Higher-order Class Label Connectivity for Heterophilous Graphs
arXiv:2606. 07475v1 Announce Type: cross Abstract: Node classification in graph neural networks (GNNs) has been widely applied in various fields of graph analysis.
arXiv Machine Learning
Jun 8
Dash2Sim: Closed-Loop Driving Simulation from in-the-wild Dashcam Videos
arXiv:2606. 07366v1 Announce Type: cross Abstract: Self-driving simulations typically rely on data collected in a small number of cities or on hand-authored synthetic scenarios.
arXiv AI
Jun 8
Quantum-Inspired Trace-Augmented Evidence Selection for Reasoning over Structured Hypothesis Spaces
arXiv:2606. 06941v1 Announce Type: new Abstract: Large language models (LLMs) now solve a wide range of expert-level exams at or above human level, yet remain brittle on specialised, evidence-intensive domains such as law.
arXiv AI
Jun 8
OffQ: Taming Structured Outliers in LLM Quantization by Offsetting
arXiv:2606. 07116v1 Announce Type: cross Abstract: Low-bit quantization has been widely adopted to accelerate the inference of large language models (LLMs) by significantly reducing computational cost and memory usage.
arXiv AI
Jun 8
Zero-Shot Embedding Drift Detection: A Lightweight Defense Against Prompt Injections in LLMs
arXiv:2601. 12359v1 Announce Type: cross Abstract: Prompt injection attacks have become an increasing vulnerability for LLM applications, where adversarial prompts exploit indirect input channels such as emails or user-generated content to circumvent alignment safeguards and induce harmful or unintended outputs.
arXiv AI
Jun 8
When Does Multi-Agent Collaboration Help? An Entropy Perspective
arXiv:2602. 04234v6 Announce Type: cross Abstract: Multi-agent systems (MAS) have emerged as a prominent paradigm for leveraging large language models (LLMs) to tackle complex tasks.
arXiv Machine Learning
Jun 8
How Far Can Chord-Symbol Time-Series Adaptation Carry Genre Identity? Capabilities and Boundaries in Multi-Genre Chord-Symbol Modeling
arXiv:2606. 07334v1 Announce Type: cross Abstract: Harmony is a compact symbolic layer where mathematical pitch relations, acoustic consonance, and musical convention meet.