SVA-ICL: Improving LLM-based Software Vulnerability Assessment via In-Context Learning and Information Fusion | Paper Citation Record

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SVA-ICL: Improving LLM-based Software Vulnerability Assessment via In-Context Learning and Information Fusion Unresolved cited work

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This paper cites Dissanayake, A.

SVA-ICL: Improving LLM-based Software Vulnerability Assessment via In-Context Learning and Information Fusion Dissanayake, A

Reference 2

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SVA-ICL: Improving LLM-based Software Vulnerability Assessment via In-Context Learning and Information Fusion Unresolved cited work

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This paper cites Vaithilingam, T.

SVA-ICL: Improving LLM-based Software Vulnerability Assessment via In-Context Learning and Information Fusion Vaithilingam, T

Reference 5

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SVA-ICL: Improving LLM-based Software Vulnerability Assessment via In-Context Learning and Information Fusion Unresolved cited work

Reference 9

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This paper cites A Survey on In-context Learning.

SVA-ICL: Improving LLM-based Software Vulnerability Assessment via In-Context Learning and Information Fusion A Survey on In-context Learning

Reference 10

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This paper cites Babalau, D.

SVA-ICL: Improving LLM-based Software Vulnerability Assessment via In-Context Learning and Information Fusion Babalau, D

Reference 11

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Reference 12

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This paper cites DeepSeek-V2: A Strong, Economical, and Efficient Mixture-of-Experts Language Model.

SVA-ICL: Improving LLM-based Software Vulnerability Assessment via In-Context Learning and Information Fusion DeepSeek-V2: A Strong, Economical, and Efficient Mixture-of-Experts Language Model

Reference 13

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This paper cites Humayun, N.

SVA-ICL: Improving LLM-based Software Vulnerability Assessment via In-Context Learning and Information Fusion Humayun, N

Reference 14

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This paper cites Common Vulnerability Scoring System.

SVA-ICL: Improving LLM-based Software Vulnerability Assessment via In-Context Learning and Information Fusion Common Vulnerability Scoring System

Reference 15

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SVA-ICL: Improving LLM-based Software Vulnerability Assessment via In-Context Learning and Information Fusion Unresolved cited work

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This paper cites National Vulnerability Database.

SVA-ICL: Improving LLM-based Software Vulnerability Assessment via In-Context Learning and Information Fusion National Vulnerability Database

Reference 18

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This paper cites Kasneci, K.

SVA-ICL: Improving LLM-based Software Vulnerability Assessment via In-Context Learning and Information Fusion Kasneci, K

Reference 19

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This paper cites Chang, X.

SVA-ICL: Improving LLM-based Software Vulnerability Assessment via In-Context Learning and Information Fusion Chang, X

Reference 20

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This paper cites Code Repair with LLMs gives an Exploration-Exploitation Tradeoff.

SVA-ICL: Improving LLM-based Software Vulnerability Assessment via In-Context Learning and Information Fusion Code Repair with LLMs gives an Exploration-Exploitation Tradeoff

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SVA-ICL: Improving LLM-based Software Vulnerability Assessment via In-Context Learning and Information Fusion Rethinking the Role of Demonstrations: What Makes In-Context Learning Work?

Reference 22

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This paper cites Gao, X.-C.

SVA-ICL: Improving LLM-based Software Vulnerability Assessment via In-Context Learning and Information Fusion Gao, X.-C

Reference 23

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SVA-ICL: Improving LLM-based Software Vulnerability Assessment via In-Context Learning and Information Fusion CodeT5: Identifier-aware Unified Pre-trained Encoder-Decoder Models for Code Understanding and Generation

Reference 24

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SVA-ICL: Improving LLM-based Software Vulnerability Assessment via In-Context Learning and Information Fusion Unresolved cited work

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SVA-ICL: Improving LLM-based Software Vulnerability Assessment via In-Context Learning and Information Fusion CodeBERT: A Pre-Trained Model for Programming and Natural Languages

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SVA-ICL: Improving LLM-based Software Vulnerability Assessment via In-Context Learning and Information Fusion Whitening Sentence Representations for Better Semantics and Faster Retrieval

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SVA-ICL: Improving LLM-based Software Vulnerability Assessment via In-Context Learning and Information Fusion Ming, Similarities: similarity calculation and semantic search toolkit, https://github.com/shibing624/similarities (2022)

Reference 29

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SVA-ICL: Improving LLM-based Software Vulnerability Assessment via In-Context Learning and Information Fusion PromptBERT: Improving BERT Sentence Embeddings with Prompts

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SVA-ICL: Improving LLM-based Software Vulnerability Assessment via In-Context Learning and Information Fusion Yujian, L

Reference 35

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SVA-ICL: Improving LLM-based Software Vulnerability Assessment via In-Context Learning and Information Fusion Watch Out for Your Guidance on Generation! Exploring Conditional Backdoor Attacks against Large Language Models

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SVA-ICL: Improving LLM-based Software Vulnerability Assessment via In-Context Learning and Information Fusion Common Vulnerabilities and Exposures

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SVA-ICL: Improving LLM-based Software Vulnerability Assessment via In-Context Learning and Information Fusion Cortes, V

Reference 47

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Reference 48

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SVA-ICL: Improving LLM-based Software Vulnerability Assessment via In-Context Learning and Information Fusion Luque, A

Reference 49

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SVA-ICL: Improving LLM-based Software Vulnerability Assessment via In-Context Learning and Information Fusion Spanos, L

Reference 50

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This paper cites Gorodkin, Comparing two k-category assignments by a k-category cor- relation coefficient, Computational biology and chemistry 28 (5-6) (2004) 367–374.

SVA-ICL: Improving LLM-based Software Vulnerability Assessment via In-Context Learning and Information Fusion Gorodkin, Comparing two k-category assignments by a k-category cor- relation coefficient, Computational biology and chemistry 28 (5-6) (2004) 367–374

Reference 51

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SVA-ICL: Improving LLM-based Software Vulnerability Assessment via In-Context Learning and Information Fusion A Comprehensive Capability Analysis of GPT-3 and GPT-3.5 Series Models

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SVA-ICL: Improving LLM-based Software Vulnerability Assessment via In-Context Learning and Information Fusion Anand, Z

Reference 53

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SVA-ICL: Improving LLM-based Software Vulnerability Assessment via In-Context Learning and Information Fusion Transformer-XL: Attentive Language Models Beyond a Fixed-Length Context

Reference 54

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Observation cac24e7c-4a36-4376-b7be-33b353564952 · outbound

This paper cites Nashid, M.

SVA-ICL: Improving LLM-based Software Vulnerability Assessment via In-Context Learning and Information Fusion Nashid, M

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:23:25.345206Z

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 169b7159-fb7b-4c60-87d3-6717fb914683 · outbound

This paper cites Binding Language Models in Symbolic Languages.

SVA-ICL: Improving LLM-based Software Vulnerability Assessment via In-Context Learning and Information Fusion Binding Language Models in Symbolic Languages

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-15T21:23:24.361564Z

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SVA-ICL: Improving LLM-based Software Vulnerability Assessment via In-Context Learning and Information Fusion Bulatov, Y

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:23:25.242029Z

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 383cd101-5495-4104-bd04-1e11609c507a · outbound

This paper cites Ahmed, K.

SVA-ICL: Improving LLM-based Software Vulnerability Assessment via In-Context Learning and Information Fusion Ahmed, K

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:23:25.144527Z

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 48992a7d-b0b7-4a88-ba96-c0471d4404e8 · outbound

This paper cites Ishizue, K.

SVA-ICL: Improving LLM-based Software Vulnerability Assessment via In-Context Learning and Information Fusion Ishizue, K

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:23:25.012049Z

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 3d4c7ae5-b725-4487-965c-4902aa27ce73 · outbound

This paper cites Do Viet, K.

SVA-ICL: Improving LLM-based Software Vulnerability Assessment via In-Context Learning and Information Fusion Do Viet, K

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:23:24.906254Z

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Observation 304d3aab-2660-4451-a839-0d3a2f526051 · outbound

This paper cites ICE-Score: Instructing Large Language Models to Evaluate Code.

SVA-ICL: Improving LLM-based Software Vulnerability Assessment via In-Context Learning and Information Fusion ICE-Score: Instructing Large Language Models to Evaluate Code

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-15T21:23:24.394985Z

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Observation c442a9b6-e688-4335-ab5d-1562c0034fb5 · outbound

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SVA-ICL: Improving LLM-based Software Vulnerability Assessment via In-Context Learning and Information Fusion DevEval: Evaluating Code Generation in Practical Software Projects

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-15T21:23:24.408692Z

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Observation 012d6b58-272d-4e4d-aee9-926ffa264ecf · outbound

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SVA-ICL: Improving LLM-based Software Vulnerability Assessment via In-Context Learning and Information Fusion Unresolved cited work

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-15T21:23:24.415348Z

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Unavailable: canonical work link unavailable.

Observation e5a453b0-4009-42ba-8abe-cd24290adbba · outbound

This paper cites Ganesh, T.

SVA-ICL: Improving LLM-based Software Vulnerability Assessment via In-Context Learning and Information Fusion Ganesh, T

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:23:24.872345Z

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 88fe8bab-9ab8-4dcf-9294-ecdb71cbc48f · outbound

This paper cites degrees in com- puter software and theory from Nanjing University in 2008 and 2011, respectively.

SVA-ICL: Improving LLM-based Software Vulnerability Assessment via In-Context Learning and Information Fusion degrees in com- puter software and theory from Nanjing University in 2008 and 2011, respectively

Reference 2002

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:23:24.852832Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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