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In-Context Learning

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TitleStatusHype
Hallucination, Monofacts, and Miscalibration: An Empirical InvestigationCode0
The Geometry of Prompting: Unveiling Distinct Mechanisms of Task Adaptation in Language Models—0
Elevating Legal LLM Responses: Harnessing Trainable Logical Structures and Semantic Knowledge with Legal ReasoningCode0
DebateBench: A Challenging Long Context Reasoning Benchmark For Large Language Models—0
MATH-Perturb: Benchmarking LLMs' Math Reasoning Abilities against Hard Perturbations—0
EquiTabPFN: A Target-Permutation Equivariant Prior Fitted Networks—0
Investigating the Zone of Proximal Development of Language Models for In-Context LearningCode0
Few-shot_LLM_Synthetic_Data_with_Distribution_MatchingCode0
Emergence of Episodic Memory in Transformers: Characterizing Changes in Temporal Structure of Attention Scores During Training—0
TabICL: A Tabular Foundation Model for In-Context Learning on Large Data—0
Technical Debt in In-Context Learning: Diminishing Efficiency in Long Context—0
In-context denoising with one-layer transformers: connections between attention and associative memory retrieval—0
Extracting and Understanding the Superficial Knowledge in AlignmentCode0
Efficient Knowledge Feeding to Language Models: A Novel Integrated Encoder-Decoder Architecture—0
BOLT: Bootstrap Long Chain-of-Thought in Language Models without Distillation—0
Short-length Adversarial Training Helps LLMs Defend Long-length Jailbreak Attacks: Theoretical and Empirical EvidenceCode0
Exploring Imbalanced Annotations for Effective In-Context Learning—0
Scalable In-Context Learning on Tabular Data via Retrieval-Augmented Large Language Models—0
Analyzing limits for in-context learning—0
Path Planning for Masked Diffusion Model Sampling—0
Is In-Context Universality Enough? MLPs are Also Universal In-Context—0
OmniRL: In-Context Reinforcement Learning by Large-Scale Meta-Training in Randomized Worlds—0
TabPFN Unleashed: A Scalable and Effective Solution to Tabular Classification Problems—0
The in-context inductive biases of vision-language models differ across modalities—0
LLM-based event log analysis techniques: A survey—0
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