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20242026
most citedUnderstand What LLM Needs: Dual Preference Alignment for Retrieval-Augmented Generation

4 citations · 8 across the 9 of their papers we have counts for

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7 papers · 1 filter

cs.IR2026

SWIM: Step-Wise Integrated Measure for Session-supervised List Evaluation in Generative Re-ranking

Yuanhao Pu, Chenghao Zhang, Chao Feng +6

Modern industrial recommender systems have increasingly adopted the Generator-Evaluator (G-E) framework for the re-ranking stage. Within this paradigm, the generator produces candi…

cs.IR2026

PSG: Pair-Space Generation for Efficient Generative Reranking

Chao Feng, Li Ma, Xiancheng Gao +3

Modern recommender systems adopt Generator-Evaluator (G-E) for list-wise reranking: a generator produces sequences from candidates and an evaluator scores them at sequence-level to…

cs.IR2026

DIRECTOR: Dynamic Index-based Recommendation with Transport-Optimized Retrieval

Yuanhao Pu, Chenghao Zhang, Chao Feng +2

Reranking is a combinatorial decision problem that aims to select and order a high-utility slate from a request-specific candidate set. A major line of generative rerankers adopts…

cs.CL2026

Towards Verifiable Multimodal Deep Research: A Multi-Agent Harness for Interleaved Report Generation

Chenghao Zhang, Guanting Dong, Yufan Liu +3

Large Language Models (LLMs) have advanced autonomous agents from deep search, which retrieves concise factual answers, to deep research, which synthesizes scattered evidence into…

cs.SD2026

ATIR: Towards Audio-Text Interleaved Contextual Retrieval

Tong Zhao, Chenghao Zhang, Yutao Zhu +1

Audio carries richer information than text, including emotion, speaker traits, and environmental context, while also enabling lower-latency processing compared to speech-to-text pi…

cs.IR2026

SOLAR: SVD-Optimized Lifelong Attention for Recommendation

Chenghao Zhang, Chao Feng, Yuanhao Pu +9

Attention mechanism remains the defining operator in Transformers since it provides expressive global credit assignment, yet its quadratic cost in sequence length N makes long-cont…

cs.IR2026

FlashEvaluator: Expanding Search Space with Parallel Sequence-Level Evaluation

Chao Feng, Yuanhao Pu, Chenghao Zhang +5

The Generator-Evaluator (G-E) framework generates K candidate sequences and uses an evaluator to select the highest-scoring one, which is widely used in recommender systems (RecSys…