most citedInternLM2 Technical Report

29 citations · 29 across the 4 of their papers we have counts for

collaborators

5 papers

cs.AI2026

MathForm: Scaling Mathematical Autoformalization with Knowledge Retrieval and Verification-Guided Refinement

Lushi Pu, Weiming Zhang, Xinheng Xie +7

Autoformalization is commonly framed as translating natural-language mathematical statements into machine-verifiable formal languages such as Lean 4. However, faithful formalizatio…

cs.AI2026

MA-ProofBench: A Two-Tiered Evaluation of LLMs for Theorem Proving in Mathematical Analysis

Lushi Pu, Weiming Zhang, Xinheng Xie +6

Large Language Models (LLMs) have made notable progress in automated theorem proving, yet existing formal benchmarks remain limited in both mathematical coverage and difficulty. Mo…

cs.CL2024

AlchemistCoder: Harmonizing and Eliciting Code Capability by Hindsight Tuning on Multi-source Data

Zifan Song, Yudong Wang, Wenwei Zhang +8

Open-source Large Language Models (LLMs) and their specialized variants, particularly Code LLMs, have recently delivered impressive performance. However, previous Code LLMs are typ…

cs.CV2024

GenEARL: A Training-Free Generative Framework for Multimodal Event Argument Role Labeling

Hritik Bansal, Po-Nien Kung, P. Jeffrey Brantingham +2

Multimodal event argument role labeling (EARL), a task that assigns a role for each event participant (object) in an image is a complex challenge. It requires reasoning over the en…

cs.CL202429 cited

InternLM2 Technical Report

Zheng Cai, Maosong Cao, Haojiong Chen +97

The evolution of Large Language Models (LLMs) like ChatGPT and GPT-4 has sparked discussions on the advent of Artificial General Intelligence (AGI). However, replicating such advan…