$Copertina$

Executable Functional Abstractions: Inferring Generative Programs for Advanced Math Problems

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Khan, Zaid, Stengel-Eskin, Elias, Prasad, Archiki, Cho, Jaemin, Bansal, Mohit
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Computation and Language Artificial Intelligence Machine Learning
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

One Life to Learn: Inferring Symbolic World Models for Stochastic Environments from Unguided Exploration
di: Khan, Zaid, et al.
Pubblicazione: (2025)

ReGAL: Refactoring Programs to Discover Generalizable Abstractions
di: Stengel-Eskin, Elias, et al.
Pubblicazione: (2024)

DataEnvGym: Data Generation Agents in Teacher Environments with Student Feedback
di: Khan, Zaid, et al.
Pubblicazione: (2024)

Rephrase, Augment, Reason: Visual Grounding of Questions for Vision-Language Models
di: Prasad, Archiki, et al.
Pubblicazione: (2023)

Learning to Generate Unit Tests for Automated Debugging
di: Prasad, Archiki, et al.
Pubblicazione: (2025)

Soft Self-Consistency Improves Language Model Agents
di: Wang, Han, et al.
Pubblicazione: (2024)

Multi-Attribute Steering of Language Models via Targeted Intervention
di: Nguyen, Duy, et al.
Pubblicazione: (2025)

Cog-DRIFT: Exploration on Adaptively Reformulated Instances Enables Learning from Hard Reasoning Problems
di: Chen, Justin Chih-Yao, et al.
Pubblicazione: (2026)

PRInTS: Reward Modeling for Long-Horizon Information Seeking
di: Lee, Jaewoo, et al.
Pubblicazione: (2025)

Retrieval-Augmented Generation with Conflicting Evidence
di: Wang, Han, et al.
Pubblicazione: (2025)

Contrastive Region Guidance: Improving Grounding in Vision-Language Models without Training
di: Wan, David, et al.
Pubblicazione: (2024)

GPU Forecasters: Language Models as Selective Surrogates for Kernel Runtime Optimization
di: Khan, Zaid, et al.
Pubblicazione: (2026)

Think Right: Learning to Mitigate Under-Over Thinking via Adaptive, Attentive Compression
di: Singh, Joykirat, et al.
Pubblicazione: (2025)

System-1.x: Learning to Balance Fast and Slow Planning with Language Models
di: Saha, Swarnadeep, et al.
Pubblicazione: (2024)

LASeR: Learning to Adaptively Select Reward Models with Multi-Armed Bandits
di: Nguyen, Duy, et al.
Pubblicazione: (2024)

AVSD: Adaptive-View Self-Distillation by Balancing Consensus and Teacher-Specific Privileged Signals
di: Nguyen, Duy, et al.
Pubblicazione: (2026)

UPCORE: Utility-Preserving Coreset Selection for Balanced Unlearning
di: Patil, Vaidehi, et al.
Pubblicazione: (2025)

Playing Along: Learning a Double-Agent Defender for Belief Steering via Theory of Mind
di: Xiao, Hanqi, et al.
Pubblicazione: (2026)

GrAInS: Gradient-based Attribution for Inference-Time Steering of LLMs and VLMs
di: Nguyen, Duy, et al.
Pubblicazione: (2025)

Skill-Based Mixture-of-Experts: Adaptive Routing for Heterogeneous Reasoning via Inferred Skills
di: Chen, Justin Chih-Yao, et al.
Pubblicazione: (2025)

GenerationPrograms: Fine-grained Attribution with Executable Programs
di: Wan, David, et al.
Pubblicazione: (2025)

Task-Circuit Quantization: Leveraging Knowledge Localization and Interpretability for Compression
di: Xiao, Hanqi, et al.
Pubblicazione: (2025)

CAPTURe: Evaluating Spatial Reasoning in Vision Language Models via Occluded Object Counting
di: Pothiraj, Atin, et al.
Pubblicazione: (2025)

RotBench: Evaluating Multimodal Large Language Models on Identifying Image Rotation
di: Niu, Tianyi, et al.
Pubblicazione: (2025)

Conflict-Resolving and Sharpness-Aware Minimization for Generalized Knowledge Editing with Multiple Updates
di: Nguyen, Duy, et al.
Pubblicazione: (2026)

Agent-BRACE: Decoupling Beliefs from Actions in Long-Horizon Tasks via Verbalized State Uncertainty
di: Singh, Joykirat, et al.
Pubblicazione: (2026)

Effective Reasoning Chains Reduce Intrinsic Dimensionality
di: Prasad, Archiki, et al.
Pubblicazione: (2026)

LACIE: Listener-Aware Finetuning for Confidence Calibration in Large Language Models
di: Stengel-Eskin, Elias, et al.
Pubblicazione: (2024)

Teaching Models to Balance Resisting and Accepting Persuasion
di: Stengel-Eskin, Elias, et al.
Pubblicazione: (2024)

Language Models Identify Ambiguities and Exploit Loopholes
di: Choi, Jio, et al.
Pubblicazione: (2025)

AdaCAD: Adaptively Decoding to Balance Conflicts between Contextual and Parametric Knowledge
di: Wang, Han, et al.
Pubblicazione: (2024)

The Sum Leaks More Than Its Parts: Compositional Privacy Risks and Mitigations in Multi-Agent Collaboration
di: Patil, Vaidehi, et al.
Pubblicazione: (2025)

EnvGen: Generating and Adapting Environments via LLMs for Training Embodied Agents
di: Zala, Abhay, et al.
Pubblicazione: (2024)

Fundamental Problems With Model Editing: How Should Rational Belief Revision Work in LLMs?
di: Hase, Peter, et al.
Pubblicazione: (2024)

DiagrammerGPT: Generating Open-Domain, Open-Platform Diagrams via LLM Planning
di: Zala, Abhay, et al.
Pubblicazione: (2023)

VideoDirectorGPT: Consistent Multi-scene Video Generation via LLM-Guided Planning
di: Lin, Han, et al.
Pubblicazione: (2023)

Are language models rational? The case of coherence norms and belief revision
di: Hofweber, Thomas, et al.
Pubblicazione: (2024)

ADaPT: As-Needed Decomposition and Planning with Language Models
di: Prasad, Archiki, et al.
Pubblicazione: (2023)

GTBench: Uncovering the Strategic Reasoning Limitations of LLMs via Game-Theoretic Evaluations
di: Duan, Jinhao, et al.
Pubblicazione: (2024)

Routing with Generated Data: Annotation-Free LLM Skill Estimation and Expert Selection
di: Niu, Tianyi, et al.
Pubblicazione: (2026)