HuggingFace
Skill Issue: Are Skills Language-Invariant in LLMs?
Large language models access knowledge inconsistently across languages, but to what extent do they differ in their sk...
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HuggingFace
GUI-Primitives: Diagnosing Spatial Reasoning Failures in Vision-Language GUI Grounding
Computer-use agents ground natural-language instructions in screenshots to locate interface elements, yet existing be...
arXiv
DualOPSD: Adaptive Privileged Teachers for On-Policy Self-Distillation
On-policy self-distillation (OPSD) uses a privileged copy of the student model to provide dense supervision without a...
arXiv
Trace Integrity for LLM Data Agents: A Vision for Auditable Structured Reasoning in Real-World Systems
Answer accuracy is an insufficient reliability signal for LLM data agents. In structured-data tasks, a benchmark-corr...
arXiv
The Value of Human Expertise
We consider optimization applications with unknown parameters where the decision maker believes that the optimal valu...
arXiv
How Much Rank Does LoRA Need? Rank-Error Bounds for Transformer Attention
Choosing the rank of a low-rank adaptation (LoRA) update is usually an empirical task. In this paper, we provide a ta...
arXiv
$R^3$: Training Robots to Reason in Natural Language via Reinforcement Learning
Reasoning in language allows foundation models to spend more test-time compute on hard problems, such as those requir...
arXiv
Prefix Sliding for efficient test-time scaling
Test-time scaling uses extra test-time compute to improve performance, such as letting language models reason longer ...
arXiv
Gating Before Commitment: Anticipating Intent Divergence to Prevent Post-Interaction Decision Failures in Autonomous Driving
Intent misinterpretation during vehicle interactions causes recurring planning failures. We study a decision layer in...
arXiv
SwarmWorld: Stigmergic technological evolution in societies of language-model agents
Collective intelligence can emerge when individuals coordinate through a shared environment, allowing local actions t...
arXiv
ICON Decomposition: Multivariate Concept-Level Explanations of Deep Representations for Model Auditing
Deep neural networks often exploit spurious associations in their training data, a failure known as shortcut learning...
arXiv
TraceML: An Empirical Analysis of Human-Agent Planning in Machine Learning Development
Large language models write correct code for isolated problems but remain far weaker at autonomous machine-learning d...