5 citations · 33 across the 40 of their papers we have counts for
41 papers
Invariant Pretraining for Robust Code Representations
Yifeng He, Yundi Xu, Christopher Castro Gaw Gonzalo +2
Encoder-based code representation models remain widely deployed for discriminative tasks such as clone detection and code classification, where their small size and low inference c…
Dynamic Surveys: Using LLMs to Blend Qualitative Depth,Quantitative Structure, and Collaborative Interaction
Kehua Lei, Aidan Ladenburg, Zahra Petiwala +5
Surveys are a powerful tool for collecting data and eliciting insights on social phenomena, and are critical in product design, marketing, scientific research. However, traditional…
CLI-Universe: Towards Verifiable Task Synthesis Engine for Terminal Agents
Zhanbo Hua, Yifan Yao, Weihao Xie +14
While recent LLM-based terminal agents have demonstrated promising capabilities, the scarcity of high-quality, executable training data remains a critical bottleneck. Existing synt…
Joint Training of Multi-Token Prediction in Reinforcement Learning via Optimal Coefficient Calibration
Zili Wang, Jiajun Chai, Lin Chen +3
Reinforcement Learning from Verifiable Rewards (RLVR) has emerged as the standard paradigm for improving reasoning capability of large language models, while Multi-Token Prediction…
OProver: A Unified Framework for Agentic Formal Theorem Proving
David Ma, Kaijing Ma, Shawn Guo +7
Recent progress in formal theorem proving has benefited from large-scale proof generation and verifier-aware training, but agentic proving is rarely integrated into prover training…
ContractBench: Can LLM Agents Preserve Observation Contracts?
Jicheng Wang, Yifeng He, Zili Wang +3
Tool-augmented LLM agents call APIs whose intermediate outputs, such as presigned URLs, session tokens, and OAuth state parameters, are observation contracts: artifacts whose later…
Visual Generation in the New Era: An Evolution from Atomic Mapping to Agentic World Modeling
Keming Wu, Zuhao Yang, Kaichen Zhang +24
Recent visual generation models have made major progress in photorealism, typography, instruction following, and interactive editing, yet they still struggle with spatial reasoning…
Beyond Sequential Distance: Inter-Modal Distance Invariant Position Encoding
Lin Chen, Bolin Ni, Qi Yang +5
Despite the remarkable capabilities of Multimodal Large Language Models (MLLMs), they still suffer from visual fading in long-context scenarios. Specifically, the attention to visu…
Step 3.5 Flash: Open Frontier-Level Intelligence with 11B Active Parameters
Ailin Huang, Ang Li, Aobo Kong +213
We introduce Step 3.5 Flash, a sparse Mixture-of-Experts (MoE) model that bridges frontier-level agentic intelligence and computational efficiency. We focus on what matters most wh…
Beyond Next-Token Alignment: Distilling Multimodal Large Language Models via Token Interactions
Lin Chen, Xiaoke Zhao, Kun Ding +9
Multimodal Large Language Models (MLLMs) demonstrate impressive cross-modal capabilities, yet their substantial size poses significant deployment challenges. Knowledge distillation…
CodeSimpleQA: Scaling Factuality in Code Large Language Models
Jian Yang, Wei Zhang, Yizhi Li +8
Large language models (LLMs) have made significant strides in code generation, achieving impressive capabilities in synthesizing code snippets from natural language instructions. H…
Diffusion Language Models are Super Data Learners
Jinjie Ni, Qian Liu, Longxu Dou +5
Under strictly controlled pre-training settings, we observe a Crossover: when unique data is limited, diffusion language models (DLMs) consistently surpass autoregressive (AR) mode…
Training Optimal Large Diffusion Language Models
Jinjie Ni, Qian Liu, Chao Du +5
We introduce Quokka, the first systematic scaling law for diffusion language models (DLMs), encompassing both compute-constrained and data-constrained regimes, and studying the key…
Taming Modality Entanglement in Continual Audio-Visual Segmentation
Yuyang Hong, Qi Yang, Tao Zhang +5
Recently, significant progress has been made in multi-modal continual learning, aiming to learn new tasks sequentially in multi-modal settings while preserving performance on previ…
OmniVideoBench: Towards Audio-Visual Understanding Evaluation for Omni MLLMs
Caorui Li, Yu Chen, Yiyan Ji +40
Recent advances in multimodal large language models (MLLMs) have demonstrated substantial potential in video understanding. However, existing benchmarks fail to comprehensively eva…
Step-3 is Large yet Affordable: Model-system Co-design for Cost-effective Decoding
StepFun, :, Bin Wang +195
Large language models (LLMs) face low hardware efficiency during decoding, especially for long-context reasoning tasks. This paper introduces Step-3, a 321B-parameter VLM with hard…
Predictable Scale: Part II, Farseer: A Refined Scaling Law in Large Language Models
Houyi Li, Wenzhen Zheng, Qiufeng Wang +8
Training Large Language Models (LLMs) is prohibitively expensive, creating a critical scaling gap where insights from small-scale experiments often fail to transfer to resource-int…
Neurosymbolic Feature Extraction for Identifying Forced Labor in Supply Chains
Zili Wang, Frank Montabon, Kristin Yvonne Rozier
Supply chain networks are complex systems that are challenging to analyze; this problem is exacerbated when there are illicit activities involved in the supply chain, such as count…
Blending Supervised and Reinforcement Fine-Tuning with Prefix Sampling
Zeyu Huang, Tianhao Cheng, Zihan Qiu +4
Existing LLMs-post-training techniques are broadly categorized into supervised fine-tuning (SFT) and reinforcement fine-tuning (RFT). Each paradigm presents a distinct trade-off: (…
Faster and Better LLMs via Latency-Aware Test-Time Scaling
Zili Wang, Tianyu Zhang, Haoli Bai +5
Test-Time Scaling (TTS) has proven effective in improving the performance of Large Language Models (LLMs) during inference. However, existing research has overlooked the efficiency…
SuperGPQA: Scaling LLM Evaluation across 285 Graduate Disciplines
P Team, Xinrun Du, Yifan Yao +94
Large language models (LLMs) have demonstrated remarkable proficiency in mainstream academic disciplines such as mathematics, physics, and computer science. However, human knowledg…
A Comprehensive Survey on Long Context Language Modeling
Jiaheng Liu, Dawei Zhu, Zhiqi Bai +34
Efficient processing of long contexts has been a persistent pursuit in Natural Language Processing. With the growing number of long documents, dialogues, and other textual data, it…
Predictable Scale: Part I, Step Law -- Optimal Hyperparameter Scaling Law in Large Language Model Pretraining
Houyi Li, Wenzhen Zheng, Qiufeng Wang +10
The impressive capabilities of Large Language Models (LLMs) across diverse tasks are now well established, yet their effective deployment necessitates careful hyperparameter optimi…
Sailor2: Sailing in South-East Asia with Inclusive Multilingual LLMs
Longxu Dou, Qian Liu, Fan Zhou +38
Sailor2 is a family of cutting-edge multilingual language models for South-East Asian (SEA) languages, available in 1B, 8B, and 20B sizes to suit diverse applications. Building on…