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arXiv:2505.23703v4 Announce Type: replace-cross Abstract: Enhancing the mathematical reasoning capabilities of LLMs has garnered significant attention in both the mathematical...
arXiv:2509.15888v3 Announce Type: replace Abstract: Adapting billion-parameter language models to a downstream task is still costly, even with parameter-efficient fine-tuning...
arXiv:2407.19638v2 Announce Type: replace Abstract: This study investigates the efficacy of Large Language Models (LLMs) in causal discovery. Using newly...
arXiv:2510.09528v1 Announce Type: new Abstract: Pre-trained transformer-based models have significantly advanced automatic speech recognition (ASR), yet they remain sensitive to...
arXiv:2510.08804v1 Announce Type: new Abstract: We present MOSAIC, a multi-agent Large Language Model (LLM) framework for solving challenging scientific coding...
SwiReasoning is a decoding-time framework that lets a reasoning LLM decide when to think in latent space and when to...
arXiv:2510.08800v1 Announce Type: new Abstract: While Large Language Models (LLMs) have demonstrated advanced reasoning capabilities, their comprehensive evaluation in general...
arXiv:2510.09032v1 Announce Type: new Abstract: As an Indo-Aryan language with limited available data, Chakma remains largely underrepresented in language models....
arXiv:2510.08825v1 Announce Type: new Abstract: Large language models (LLMs) have demonstrated impressive reasoning abilities yet remain unreliable on knowledge-intensive, multi-hop...
Collaborative Multi-Agent Test-Time Reinforcement Learning for Reasoning
Cohere Releases Tiny Aya: A 3B-Parameter Small Language Model that Supports 70 Languages and Runs Locally Even on a Phone
Cognitive Surgery: The Awakening of Implicit Territorial Awareness in LLMs
Cognitive Kernel-Pro: A Framework for Deep Research Agents and Agent Foundation Models Training
Cognitive BASIC: An In-Model Interpreted Reasoning Language for LLMs
Codev lets enterprises avoid vibe coding hangovers with a team of agents that generate and document code
Code2Doc: A Quality-First Curated Dataset for Code Documentation
CoCoTen: Detecting Adversarial Inputs to Large Language Models through Latent Space Features of Contextual Co-occurrence Tensors
Co-AttenDWG: Co-Attentive Dimension-Wise Gating and Expert Fusion for Multi-Modal Offensive Content Detection
CMCTS: A Constrained Monte Carlo Tree Search Framework for Mathematical Reasoning in Large Language Model
Clustering Unstructured Text with LLM Embeddings and HDBSCAN
